Brain machine interface provides a communication channel between the human brain and an external device. Brain interfaces are studied to provide rehabilitation to patients with neurodegenerative diseases; such patients loose all communication pathways except for their sensory and cognitive functions. One of the possible rehabilitation methods for these patients is to provide a brain machine interface (BMI) for communication; the BMI uses the electrical activity of the brain detected by scalp EEG electrodes. Classification of EEG signals extracted during mental tasks is a technique for designing a BMI. In this paper a BMI design using five mental tasks from two subjects were studied, a combination of two tasks is studied per subject. An Elman recurrent neural network is proposed for classification of EEG signals. Two feature extraction algorithms using overlapped and non overlapped signal segments are analyzed. Principal component analysis is used for extracting features from the EEG signal segments. Classification performance of overlapping EEG signal segments is observed to be better in terms of average classification with a range of 78.5% to 100%, while the non overlapping EEG signal segments show better classification in terms of maximum classifications.
The electrical load is affected by the weather conditions in many countries as well as in Iraq. The weather-sensitive electrical load is, usually, divided into two components, a weather-sensitive component, and a weather-insensitive component. The research provides a method for separating the weather-sensitive electrical load into five components. and aims to prove the efficiency of the five-component load Forecasting model. The artificial neural network was used to predict the weather-sensitive electrical load using the MATLAB R17a software. Weather data and loads were used for one year for Mosul City. The performance of the artificial neural network was evaluated using the mean squared error and the mean absolute percentage error. The results indicate the accuracy of the prediction model used, MAPE equal to 0.0402.
This paper presents a new optimization algorithm called corrosion diffusion optimization algorithm (CDOA). The proposed algorithm is based on the diffusion behavior of the pitting corrosion on the metal surface. CDOA utilizes the oxidation and reduction electrochemical reductions as well as the mathematical model of Gibbs free energy in its searching for the optimal solution of a certain problem. Unlike other algorithms, CDOA has the advantage of dispensing any parameter that need to be set for improving the convergence toward the optimal solution. The superiority of the proposed algorithm over the others is highlighted by applying them on some unimodal and multimodal benchmark functions. The results show that CDOA has better performance than the other algorithms in solving the unimodal equations regardless the dimension of the variable. On the other hand, CDOA provides the best multimodal optimization solution for dimensions less than or equal to (5, 10, 15, up to 20) but it fails in solving this type of equations for variable dimensions larger than 20. Moreover, the algorithm is also applied on two engineering application problems, namely the PID controller and the cantilever beam to accentuate its high performance in solving the engineering problems. The proposed algorithm results in minimized values for the settling time, rise time, and overshoot for the PID controller. Where the rise time, settling time, and maximum overshoot are reduced in the second order system to 0.0099, 0.0175 and 0.005 sec., in the fourth order system to 0.0129, 0.0129 and 0 sec, in the fifth order system to 0.2339, 0.7756 and 0, in the fourth system which contains time delays to 1.5683, 2.7102 and 1.80 E-4 sec., and in the simple mass-damper system to 0.403, 0.628 and 0 sec., respectively. In addition, it provides the best fitness function for the cantilever beam problem compared with some other well-known algorithms.
This paper discusses the design and performance of a frequency reconfigurable antenna for Internet of Things (IoT) applications. The antenna is designed to operate on multiple frequency bands and be reconfigurable to adjust to different communication standards and environmental conditions. The antenna design consists of monopole with one PIN diode and 50Ωfeed line. By changing the states of the diode, the antenna can be reconfigured to operate in a dual-band mode and a wideband mode. The performance of the antenna was evaluated through simulation. The antenna demonstrated good impedance matching, acceptable gain, and stable radiation patterns across the different frequency bands. The antenna has compact dimensions of (26×19×1.6) mm3. It covers the frequency range 2.95 GHz -8.2 GHz, while the coverage of the dual- band mode is (2.7-3.8) GHz and (4.57-7.4) GHz. The peak gain is 1.57 dBi for the wideband mode with omnidirectional radiation pattern. On the other hand, the peak gain of the dual-band mode is 0.87 dBi at 3 GHz and 0.47 dBi at 6 GHz with an omnidirectional radiation pattern too.
The tremendous development in the field of communications is derived from the increasing demand for fast transmission and processing of huge amounts of data. The non-orthogonal multiple access (NOMA) system was proposed to increase spectral efficiency (SE) and improve energy efficiency (EE) as well as contribute to preserving the environment and reducing pollution. In the NOMA system, a user may be considered as a relay to the others that support the coverage area based on adopting the reuse of the frequency technique. This cooperation enhances the spectral efficiency, however, in the cell, there are other users that may affect the spectral allocation that should be taken into consideration. Therefore, this paper is conducted to analyze the case when three users are available to play as relies upon. The analyses are performed in terms of the transmitted power allocation in a fair manner, and the system's performance is analyzed using the achievable data rates and the probability of an outage. The results showed an improvement in throughputs for the second and third users, as its value ranged from 7.57 bps/Hz to 12.55 bps/Hz for the second user and a quasi-fixed value of 1,292 bps/Hz for the third user at the transmitted power ranging from zero to 30 dBm.
The paper dells with a modified experimental prototype for pulse-width modulation (PWM) sliding mode control (SMC) applied to a DC-to-DC-boost converter operated in continuous conduction mode (CCM). Experimental results show that the proposed control schme provides good voltage regulation and is suitable for common DC-to-DC conversion purposes. The prototype and its implementation are given in detail. The static and dynamic performances of the The static and dynamic performances of the experimental system are recorded. Experimental results show that the proposed control scheme provides good voltage regulation and is suitable for common DC-to-DC conversion purposes.
Large disturbances in an induction generator-based wind system necessitate rapid compensation for the reactive power. This article addresses the application of Static Synchronous Compensator (STATCOM) in optimizing the performance of grid connected wind power system. The functionality of the static synchronous compensator in maintaining system stability and reliability during/post diverse severe disturbances is thoroughly investigated. A design procedure for STATCOM, particularly the capacitor in the DC side was advised.
The dynamic performance of vertical-cavity surface emitting lasers (VCSEL) diodes can be enhanced by incorporating multiquantum-well (MQW) structure in the active region. This paper addresses the transient response of MQW-VCSEL by solving the laser rate equation in the large-signal regime. The analysis makes use of the energy band structure and optical gain spectrum obtained by applying Schrödinger equation to both conduction and valance bands. Simulation results are presented for $1.3~\mu m$ InGaAs/InP VCSEL and indicate clearly that a MQW laser has higher switching speed compared with bulk laser and this finding is more pronounced with small number of wells.
The Permanent Magnet Synchronous Motor (PMSM) is commonly used as traction motors in the electric traction applications such as in subway train. The subway train is better transport vehicle due to its advantages of security, economic, health and friendly with nature. Braking is defined as removal of the kinetic energy stored in moving parts of machine. The plugging braking is the best braking offered and has the shortest time to stop. The subway train is a heavy machine and has a very high moment of inertia requiring a high braking torque to stop. The plugging braking is an effective method to provide a fast stop to the train. In this paper plugging braking system of the PMSM used in the subway train in normal and fault-tolerant operation is made. The model of the PMSM, three-phase Voltage Source Inverter (VSI) controlled using Space Vector Pulse Width Modulation technique (SVPWM), Field Oriented Control method (FOC) for independent control of two identical PMSMs and fault-tolerant operation is presented. Simulink model of the plugging braking system of PMSM in normal and fault tolerant operation is proposed using Matlab/Simulink software. Simulation results for different cases are given.
Electrical issues such as old wires and faulty connections are the most common causes of arc faults. Arc faults cause electrical fires by generating high temperatures and discharging molten metal. Every year, such fires cause a considerable deal of destruction and loss. This paper proposes a new method for detecting residential series and parallel arc faults. A simulation model for the arc is employed to simulate the arc faults in series and parallel circuits. The fault features are then retrieved using a signal processing approach called Discrete Wavelet Transform (DWT) designed in MATLAB/Simulink based on the fault detection algorithm. Then db2 and one level were found appropriate mother and level of wavelet transform for extracting arc-fault features. MATLAB Simulink was used to build and simulate the arc-fault model.
The residential electrical load in the city of Mosul as well as in most of cities in Iraq, is the major problem for the administration of electricity distribution. Since this kind of load is increasing drastically compared with other loads such as industrial, agricultural tourism and others which are declining for the last two decades due to unstable condition of the county. The residential electrical load components must be determined to solve the problems resulting from the significant increase in this load. This research aims to conduct a field survey to find out and identify the components of the residential electrical load ratios and qualitative change in the months of the year. The survey was conducted in the city of Mosul in northern Iraq. T he results were analyzed, and a number of recommendations were given to rationalize consumption.
Bin picking robots require vision sensors capable of recognizing objects in the bin irrespective of the orientation and pose of the objects inside the bin. Bin picking systems are still a challenge to the robot vision research community due to the complexity of segmenting of occluded industrial objects as well as recognizing the segmented objects which have irregular shapes. In this paper a simple object recognition method is presented using singular value decomposition of the object image matrix and a functional link neural network for a bin picking vision system. The results of the functional link net are compared with that of a simple feed forward net. The network is trained using the error back propagation procedure. The proposed method is robust for recognition of objects.
In this paper, we evaluate the performance of UMTS (Universal Mobile Telecommunication System) downlink system in vicinity of UWB system. The study is achieved via simulating a scenario of a building which is located within UMTS cell borders and utilizes from both UMTS and UWB appliances. The simulation results show that the UMTS system is considerably affected by the UWB interference. However, in order to battle this interference and achieve reasonable BER (Bit Error Rate) of 10 -4 , we found that it is very necessary to carefully raise the UMTS base station transmitted power against that of UWB interferer. So, the minimum requirements for UMTS system to overcome UWB interference are stated in this work.
In recent years, symbolic analysis has become a well-established technique in circuit analysis and design. The symbolic expression of network characteristics offers convenience for frequency response analysis, sensitivity computation, and fault diagnosis. The aim of the paper is to present a method for symbolic analysis that depends on the use of the wavelet transform (WT) as a tool to accelerate the solution of the problem as compared with the numerical interpolation method that is based on the use of the fast Fourier transform (FFT).
In recent years, symbolic analysis has become a well-established technique in circuit analysis and design. The symbolic expression of network characteristics offers convenience for frequency response analysis, sensitivity computation, and fault diagnosis. The aim of the paper is to present a method for symbolic analysis that depends on the use of the wavelet transform (WT) as a tool to accelerate the solution of the problem as compared with the numerical interpolation method that is based on the use of the fast Fourier transform (FFT).
Some engineering applications requires constant engine speed such as power generators, production lines ..etc. The current paper focuses on adding a new closed loop based on engine torque. Load cells can be used to measure the torque of load applied , the electrical signal is properly handled to manipulate a special fuel actuator to compensate for the reduction in engine speed. The speed loop still acts as the most outer closed loop. This method leads to rapid speed compensation and lead control action.
Parallel manipulators have a rigid structure and can pick up the heavy objects. Therefore, a parallel manipulator has been developed based on the cooperative of three arms of a robotic system to make the whole system suitable for solving many problems such as materials handling and industrial automation. The three revolute joints are used to achieve the mechanism operation of the parallel planar robot. Those revolute joints are geometrically designed using an open-loop spatial robotic platform. In this paper, the geometric structure with three revolute joints is used to drive and analyze the inverse kinematic model for the 3RRR parallel planar robot. In the proposed design, three main variables are considered: the length of links of the 3RRR parallel planar robot, base positions of the platform, and joint angles’ geometry. Cayley-Menger determinants and bilateration are proposed to calculate these three variables to determine the final position of the platform and to move specific objects according to given desired trajectories. The proposed structure of the 3RRR parallel planar robot is simulated and different desired trajectories are tested to study the performance of the proposed stricter. Furthermore, the hardware implementation of the proposed structure is accomplished to validate the design in practical terms.
Power transformer protective relay should block the tripping during magnetizing inrush and rapidly operate the tripping during internal faults. Recently, the frequency environment of power system has been made more complicated and the quantity of 2nd frequency component in inrush state has been decreased because of the improvement of core steel. And then, traditional approaches will likely be maloperated in the case of magnetizing inrush with low second harmonic component and internal faults with high second harmonic component. This paper proposes a new relaying algorithm to enhance the fault detection sensitivities of conventional techniques by using a fuzzy logic approach. The proposed fuzzy-based relaying algorithm consists of flux-differential current derivative curve, harmonic restraint, and percentage differential characteristic curve. The proposed relaying was tested with MATLAB simulation software and showed a fast and accurate trip operation.
Self-organizing systems arise in many different fields. In this work we analyze data from social and biological systems. A central question is to demonstrate the presence of the determinism in time-series extracted from such systems that appear apparently not correlated but that are two good benchmarks for the study of complexity in real systems. We will apply the Kaplan test and we will define an order parameter for the biological data to characterize the complexity of the system.
In modern robotic field, many challenges have been appeared, especially in case of a multi-robot system that used to achieve tasks. The challenges are due to the complexity of the multi-robot system, which make the modeling of such system more difficult. The groups of animals in real world are an inspiration for modeling of a multi- individual system such as aggregation of Artemia. Therefore, in this paper, the multi-robot control system based on external stimuli such as light has been proposed, in which the feature of tracking Artemia to the light has been employed for this purpose. The mathematical model of the proposed design is derived and then Simulated by V-rep software. Several experiments are implemented in order to evaluate the proposed design, which is divided into two scenarios. The first scenario includes simulation of the system in situation of attraction of robot to fixed light spot, while the second scenario is the simulation of the system in the situation of the robots tracking of the movable light spot and formed different patterns like a straight-line, circular, and zigzag patterns. The results of experiments appeared that the mobile robot attraction to high-intensity light, in addition, the multi-robot system can be controlled by external stimuli. Finally, the performance of the proposed system has been analyzed.
This paper describes the capability of artificial neural network for predicting the critical clearing time of power system. It combines the advantages of time domain integration schemes with artificial neural network for real time transient stability assessment. The training of ANN is done using selected features as input and critical fault clearing time (CCT) as desire target. A single contingency was applied and the target CCT was found using time domain simulation. Multi layer feed forward neural network trained with Levenberg Marquardt (LM) back propagation algorithm is used to provide the estimated CCT. The effectiveness of ANN, the method is demonstrated on single machine infinite bus system (SMIB). The simulation shows that ANN can provide fast and accurate mapping which makes it applicable to real time scenario.
The Leader detecting and following are one of the main challenges in designing a leader-follower multi-robot system, in addition to the challenge of achieving the formation between the robots, while tracking the leader. The biological system is one of the main sources of inspiration for understanding and designing such multi-robot systems, especially, the aggregations that follow an external stimulus such as light. In this paper, a multi-robot system in which the robots are following a spotlight is designed based on the behavior of the Artemia aggregations. Three models are designed: kinematic and two dynamic models. The kinematic model reveals the light attraction behavior of the Artemia aggregations. The dynamic model will be derived based on the newton equation of forces and its parameters are evaluated by two methods: first, a direct method based on the physical structure of the robot and, second, the Least Square Parameter Estimation method. Several experiments are implemented in order to check the success of the three proposed systems and compare their performance. The experiments are divided into three scenarios of simulation according to three paths: the straight line, circle, zigzag path. The V-Rep software has been used for the simulation and the results appeared the success of the proposed system and the high performance of tracking the spotlight and achieving the flock formation, especially the dynamic models.
The PH regulation of cooling tower plant in southern fertilizers company (SCF) in Iraq is important for industry pipes protection and process continuity. According to the Mitsubishi standard, the PH of cooling water must be around (7.1 to 7.8). The deviation in PH parameter affects the pipes, such as corrosion and scale. Acidic water causes pipes to corrode, and alkaline water causes pipes to scale. The sulfuric acid solution is used for PH neutralization. The problem is that the sulfuric acid is pumped manually in the cooling tower plant every two or three hours for PH regulation. The manual operation of the sulfuric acid pump makes deviations in the PH parameter. It is very difficult to control the PH manually. To solve this problem, a PID controller for PH regulation was used. The reason for using the PID controller is that the PH response is irregular through the neutralization process. The methodology is to calculate the transfer function of the PH loop using the system identification toolbox of MATLAB, to design and implement a PID controller, to optimize the PID controller response using particle swarm optimization PSO algorithm, and to make a comparison among several tuning methods such as Ziegler Nichols (ZN) tuning method, MATLAB tuner method, and PSO algorithm tuning method. The results showed that the PSO-based PID controller tuning gives a better overshoot, less rise time, and an endurable settling time than the other tuning methods. Hence, the PH response became according to the target range. The experimental results showed that the PH regulation improved using the PSO-based PID controller tuning.
The main problem of line follower robot is how to make the mobile robot follows a desired path (which is a line drawn on the floor) smoothly and accurately in shortest time. In this paper, the design and implementation of a complex line follower mission is presented by using Matlab Simulink toolbox. The motion of mobile robot on the complex path is simulated by using the Robot Simulator which is programed in Matlab to design and test the performance of the proposed line follower algorithm and the designed PID controller. Due to the complexity of selection the parameters of PID controller, the Particle Swarm Optimization (PSO) algorithm are used to select and tune the parameters of designed PID controller. Five Infrared Ray (IR) sensors are used to collect the information about the location of mobile robot with respect to the desired path (black line). Depending on the collected information, the steering angle of the mobile robot will be controlled to maintain the robot on the desired path by controlling the speed of actuators (two DC motors). The obtained simulation results show that, the motion of mobile robot is still stable even the complex maneuver is performed. The hardware design of the robot system is perform by using the Arduino Mobile Robot (AMR). The Simulink Support Package for Arduino and control system toolbox are used to program the AMR. The practical results show that the performances of real mobile robot are exactly the same of the performances of simulated mobile robot.
Multi-level inverters, as a result of the significant contributions they have made to the fields of high voltage and renewable energy applications, MLI has earned a prestigious place in the field of industrial electronics applications. The use of MLI makes it possible to generate an alternating voltage from a DC voltage or from voltages that are continuously applied thanks to this capability. The quality of the produced wave depends on minimizing the level of total harmonic distortion (THD) in the ensuing output voltage. Increasing the total number of levels is required in order to bring down the THD. The bigger the number of layers, the lower the THD. On the other hand, this necessitates an increase in the number of power switches that are utilized, in addition to an increase in the number of DC sources for certain types. A greater number of levels are achieved in this work with a reduced number of switches, and the DC source necessitates the use of specialized control over the switches as well as the grading of the DC source values. In order to demonstrate that the suggested converter achieves the needed outcomes, the MATLAB simulator is utilized.
Arc problems are most commonly caused by electrical difficulties such as worn cables and improper connections. Electrical fires are caused by arc faults, which generate tremendous temperatures and discharge molten metal. Every year, flames of this nature inflict a great lot of devastation and loss. A novel approach for identifying residential series and parallel arc faults is presented in this study. To begin, arc faults in series and parallel are simulated using a suitable simulation arc model. The fault characteristics are then recovered using a signal processing technique based on the fault detection technique called Discrete Wavelet Transform (DWT), which is built in MATLAB/Simulink. Then came db2, and one level was discovered for obtaining arc-fault features. The suitable mother and level of wavelet transform should be used, and try to compare results with conventional methods (FFT-Fast Fourier Transform). MATLAB was used to build and simulate arc-fault models with these techniques.
The electrical consumption in Basra is extremely nonlinear; so forecasting the monthly required of electrical consumption in this city is very useful and critical issue. In this Article an intelligent techniques have been proposed to predict the demand of electrical consumption of Basra city. Intelligent techniques including ANN and Neuro-fuzzy structured trained. The result obtained had been compared with conventional Box-Jenkins models (ARIMA models) as a statistical method used in time series analysis. ARIMA (Autoregressive integrated moving average) is one of the statistical models that utilized in time series prediction during the last several decades. Neuro- Fuzzy Modeling was used to build the prediction system, which give effective in improving the predict operation efficiency. To train the prediction system, a historical data were used. The data representing the monthly electric consumption in Basra city during the period from (Jan 2005 to Dec 2011). The data utilized to compare the proposed model and the forecasting of demand for the subsequent two years (Jan 2012-Dec 2013). The results give the efficiency of proposed methodology and show the good performance of the proposed Neuro-fuzzy method compared with the traditional ARIMA method.
This review article puts forward the phenomena of chaotic oscillation in electrical power systems. The aim is to present some short summaries written by distinguished researchers in the field of chaotic oscillation in power systems. The reviewed papers are classified according to the phenomena that cause the chaotic oscillations in electrical power systems. Modern electrical power systems are evolving day by day from small networks toward large-scale grids. Electrical power systems are constituted of multiple inter-linked together elements, such as synchronous generators, transformers, transmission lines, linear and nonlinear loads, and many other devices. Most of these components are inherently nonlinear in nature rendering the whole electrical power system as a complex nonlinear network. Nonlinear systems can evolve very complex dynamics such as static and dynamic bifurcations and may also behave chaotically. Chaos in electrical power systems is very unwanted as it can drive system bus voltage to instability and can lead to voltage collapse and ultimately cause a general blackout.
In the present-day decade, the world has regarded an expansion in the use of non-linear loads. These a lot draw harmonic non- sinusoidal currents and voltages in the connection factor with the utility and distribute them with the useful resource of the overall performance of it. The propagation of these currents and voltages into the grids have an effect on the electricity constructions in addition to the one of various client equipment. As a result, the electrical strength notable has come to be critical trouble for each client and distributor of electrical power. Active electrical electricity filters have been proposed as environment splendid gear for electrical power pinnacle notch enchantment and reactive electrical strength compensation. Active Power Filters (APFs) have Flipped out to be a possible wish in mitigating the harmonics and reactive electrical electricity compensation in single-phase and three-phase AC electrical energy networks with Non-Linear Loads (NLLs). Conventionally, this paper applied Ant Colony Algorithm (ACO) for tuning PI and reduce Total Harmonic Distortion (THD). The result show reduces THD at 2.33%.
Among all control methods for induction motor drives, Direct Torque Control (DTC) seems to be particularly interesting being independent of machine rotor parameters and requiring no speed or position sensors. The DTC scheme is characterized by the absence of PI regulators, coordinate transformations, current regulators and PWM signals generators. In spite of its simplicity, DTC allows a good torque control in steady state and transient operating conditions to be obtained. However, the presence of hysterics controllers for flux and torque could determine torque and current ripple and variable switching frequency operation for the voltage source inverter. This paper is aimed to analyze DTC principles, and the problems related to its implementation, especially the torque ripple and the possible improvements to reduce this torque ripple by using a proposed fuzzy based duty cycle controller. The effectiveness of the duty ratio method was verified by simulation using Matlab/Simulink software package. The results are compared with that of the traditional DTC models.
This paper proposes a new design of compact coplanar waveguide (CPW) fed -super ultra-wideband (S-UWB) MIMO antenna with a bandwidth of 3.6 to 40 GHz. The proposed antenna is composed of two orthogonal sector-shape monopoles (SSM) antenna elements to perform polarization diversity. In addition, a matched L-shaped common ground element is attached for more efficient coupling. The FR-4 substrate of the structure with a size of 23 × 45 × 1.6 mm3 and a dielectric constant of 4.3 is considered. The proposed design is simulated by using CST Microwave Studio commercial software. The simulation shows that the antenna has low mutual coupling (|S21| < -20 dB) with |S11|<−10 dB, ranging from 3.6 to 40 GHz. Envelope correlation coefficient (ECC) is less than 0.008, diversity gain (DG) is more than 9.99, mean effective gain (MEG) is below - 3 dB and total active reflection coefficient (TARC) is less than -6 dB over the whole response band is reported. The proposed MIMO antenna is expected efficiently cover the broadest range of frequencies for contemporary communications applications.
This paper suggests the use of the traditional proportional-integral-derivative (PID) controller to control the speed of multi Permanent Magnet Synchronous Motors (PMSMs). The PMSMs are commonly used in industrial applications due to their high steady state torque, high power, high efficiency, low inertia and simple control of their drives compared to the other motors drives. In the present study a mathematical model of three phase four poles PMSM is given and simulated. The closed loop speed control for this type of motors with voltage source inverter and abc to dq blocks are designed. The multi (Master/Slaves approach) method is proposed for PMSMs. Mathwork's Matlab/Simulink software package is selected to implement this model. The simulation results have illustrated that this control method can control the multi PMSMs successfully and give better performance.
In this work, the collective behavior of Artemia Salina is studied both experimentally and theoretically. Several experiments have been designed to investigate the Artemia motion under different environment conditions. From the results of such experiments, a strategy to control the direction of motion of an Artemia population, by exploiting their sensitivity to light, has been derived and then implemented.
Induction Motors have been used as the workhorse in the industry for a long time due to its easy build, high robustness, and generally satisfactory efficiency. However, they are significantly more difficult to control than DC motors. One of the problems which might cause unsuccessful attempts for designing a proper controller would be the time varying nature of parameters and variables which might be changed while working with the motion systems. One of the best suggested solutions to solve this problem would be the use of Sliding Mode Control (SMC). This paper presents the design of a new controller for a vector control induction motor drive that employs an outer loop speed controller using SMC. Several tests were performed to evaluate the performance of the new controller method, and two other sliding mode controller techniques. From the comparative simulation results, one can conclude that the new controller law provides high performance dynamic characteristics and is robust with regard to plant parameter variations.
This paper presents a method of generating realistic electricity load profile data for the UK domestic buildings. The domestic space features have been investigated excluding the heating and hot water systems. A questionnaire survey was conducted and the feedback were collected from a number of occupants at different intervals of times on daily bases in order to establish the probabilistic record of the estimated use of electrical appliances. The model concept of this study also considers the results of previous investigations such as that available in public reports and statistics as input data elements to predict the global domestic energy consumption. In addition, the daily load profile from individual dwelling to community can be predicted using this method. The result of the present method was compared to available published data and has shown reasonable agreement.
Induction Motor (IM) speed control is an area of research that has been in prominence for some time now. In this paper, a nonlinear controller is presented for IM drives. The nonlinear controller is designed based on input-output feedback linearization control technique, combined with sliding mode control (SMC) to obtain a robust, fast and precise control of IM speed. The input-output feedback linearization control decouples the flux control from the speed control and makes the synthesis of linear controllers possible. To validate the performances of the proposed control scheme, we provided a series of simulation results and a comparative study between the performances of the proposed control strategy and those of the feedback linearization control (FLC) schemes. Simulation results show that the proposed control strategy scheme shows better performance than the FLC strategy in the face of system parameters variation.
In developing nations, such as Iraq, supplying power to isolated and rural border areas that are not connected to the grid continues to be a problem. At present, fossil fuels, which are significant causes of pollution, supply around 80% of the world’s energy demands. Nonetheless, drastically reducing reliance on fossil fuels has many reasons, including depleting global fossil fuel supplies, increasing costs and growing energy needs. The present study examines the electrical requirements of the Al-Teeb area, a city situated in the eastern region of Iraq, close to the Iranian border. This region has not been researched despite its tourism and oil significance. Despite the unpredictable expansion of many isolated locations in Iraq in recent years, the number of generation stations has not changed. Supplying energy to these places will require considerable time and money. Photovoltaics (PV), wind turbines (WTs), diesel generators (DGs), batteries and converters combined on the basis of their compatibility under three distinct scenarios comprise the system’s components. Considering the lowest net present cost (NPC) and cost of energy (COE) of all the examined scenarios, PV, WTs, batteries and DGs are the most economical solutions for the Al-Teeb area. Number of PV (1,215), number of WTs (59), number of DGs (13), number of batteries (3,138), number of converters (47), COE (0.155 US$/kWh), NPC (14.2 million US$) and initial capital cost (4.91 million US$) are revealed by the results. Finally, the results are confirmed using another global optimization method, namely, modified particle swarm optimization.
Control of Induction Motor (IM) is well known to be difficult owing to the fact the models of IM are highly nonlinear and time variant. In this paper, to achieve accurate control performance of rotor position control of IM, a new method is proposed by using adaptive inverse control (AIC) technique. In recent years, AIC is a very vivid field because of its advantages. It is quite different from the traditional control. AIC is actually an open loop control scheme and so in the AIC the instability problem cased by feedback control is avoided and the better dynamic performances can also be achieved. The model of IM is identified using adaptive filter as well as the inverse model of the IM, which was used as a controller. The significant of using the inverse of the IM dynamic as a controller is to makes the IM output response to converge to the reference input signal. To validate the performances of the proposed new control scheme, we provided a series of simulation results.
The coordination of overcurrent relay protection in the power framework is crucial for preserving electrical distribution systems. It ensures that both primary and backup protection are provided to the system. It is essential to maintain a minimal level of coordination between these relays in order to reduce the overall running time and guarantee that power outages and damage are kept to a minimum under fault conditions. Proper coordination between the primary and back-up relays can minimize the operation duration of overcurrent with instantaneous and earth fault relays by selecting the optimum TMS (Time Multiplier Setting) and PS (Plug Setting). The present study investigates the difficulty associated with determining the TMS and PS values of earth-fault and overcurrent relays at the 33/11 kV power distribution substation in Basra using the instantaneous setting element. Overcurrent and earth fault relays were simulated in two scenarios: one with a time delay setting and one with an immediate setting. This procedure was carried out to generate Time Current Characteristics (TCC) curves for each Circuit Breaker (CB) relay took place in the Nathran substation, which has a capacity of 2×31.5 MVA and operates at a voltage level of 33/11 kV. The substation is a part of the Basrah distribution network. The short circuit current is estimated at each circuit breaker (CB), followed by the simulation of protection coordination for the Nathran substation using the DIgSILENT Power Factory software. This research is based on real data collection, and the setting considers the short-circuit current at the farthest point of the longest feeders. The results show the effectiveness of the proposed coordination scheme, which reduced trip operation time by 20% compared to the presented case study while maintaining coordination between primary and backup protection.
The power theft is one of the main problems facing the electric energy sector in Iraq, where a large amount of electrical energy is lost due to theft. It is required to design a system capable of detecting and locating energy theft without any human interaction. This paper presents an effective solution with low cost to solve power theft issue in distribution lines. Master meter is designed to measures the power of all meters of the homes connected to it. All the measured values are transmitted to the server via GPRS. The values of power for all energy meters within the grid are also transmitted. The comparison between the power of the master meter and all the other meters are transmitted to the server. If there is a difference between the energy meters, then a theft is happened and the server will send a signal via GSM to the overrun meter to switch off the power supply. Raspberry pi is used as a server and equipped and programmed to detect the power theft.
In recent years, increased importance of Smart Grid, which includes monitoring and control the consumption of customers of electric power. In this paper, Wireless Smart Electrical Power Meter has been designed and implemented which ZigBee wireless sensor network (WSN) will be used for wireless electrical power meter communication supported by PIC microcontroller which used for power unit measurements. PIC microcontroller will be used for evaluating all electric power parameters at costumer side like V rms , I rms , KWh, and PF, and then all these parameters will be send to base station through wireless network in order to be calibrated and monitored.
In this paper, a two-dimensional (2-D) circular-support wavelet transform (2-D CSWT) is presented. 2-D CSWT is a new geometrical image transform, which can efficiently represent images using 2-D circular spectral split schemes (circularly- decomposed frequency subspaces). 2-D all-pass functions and lattice structure are used to produce 1-level circular symmetric 2-D discrete wavelet transform with approximate linear phase 2-D filters. The classical one-dimensional (1-D) analysis Haar filter bank branches H 0 (z) and H 1 (z) which work as low-pass and high-pass filters, respectively are transformed into their 2-D counterparts H 0 (z 1 ,z 2 ) and H 1 (z 1 ,z 2 ) by applying a circular-support version of the digital spectral transformation (DST). The designed 2-D wavelet filter bank is realized in a separable architecture. The proposed architecture is simulated using Matlab program to measure the deflection ratio (DR) of the high frequency coefficient to evaluate its performance and compare it with the performance of the classical 2-D wavelet architecture. The correlation factor between the input and reconstructed images is also calculated for both architectures. The FPGA (Spartan-3E) Kit is used to implement the resulting architecture in a multiplier-less manner and to calculate the die area and the critical path or maximum frequency of operation. The achieved multiplier-less implementation takes a very small area from FPGA Kit (the die area in 3-level wavelet decomposition takes 300 slices with 7% occupation ratio only at a maximum frequency of 198.447 MHz).
The monitoring of COVID-19 patients has been greatly aided by the Internet of Things (IoT). Vital signs, symptoms, and mobility data can be gathered and analyzed by IoT devices, including wearables, sensors, and cameras. This information can be utilized to spot early infection symptoms, monitor the illness’s development, and stop the virus from spreading. It’s critical to take vital signs of hospitalized patients in order to assess their health. Although early warning scores are often calculated three times a day, they might not indicate decompensation symptoms right away. Death rates are higher when deterioration is not properly diagnosed. By employing wearable technology, these ongoing assessments may be able to spot clinical deterioration early and facilitate prompt therapies. This research describes the use of Internet of Things (IoT) to follow fatal events in high-risk COVID-19 patients. These patients’ vital signs, which include blood pressure, heart rate, respiration rate, blood oxygen level, and fever, are taken and fed to a central server on a regular basis so that information may be processed, stored, and published instantly. After processing, the data is utilized to monitor the patients’ condition and send Short Message Service (SMS) alerts when the patients’ vital signs rise above predetermined thresholds. The system’s design, which is based on two ESP32 controllers, sensors for the vital signs listed above, and a gateway, provides real-time reports, high-risk alerts, and patient status information. Clinicians, the patient’s family, or any other authorized person can keep an eye on and follow the patient’s status at any time and from any location. The main contribution in this work is the designed algorithm used in the gateway and the manner in which this gateway collects, analyze, process, and send the patient’s data to the IoT server from one side and the manner in which the gateway deals with the IoT server in the other side. The proposed method leads to reduce the cost and the time the system it takes to get the patient’s status report.
According to the growing interest in the soft robotics research field, where various industrial and medical applications have been developed by employing soft robots. Our focus in this paper will be the Pneumatic Muscle Actuator (PMA), which is the heart of the soft robot. Achieving an accurate control method to adjust the actuator length to a predefined set point is a very difficult problem because of the hysteresis and nonlinearity behaviors of the PMA. So the construction and control of a 30 cm soft contractor pneumatic muscle actuator (SCPMA) were done here, and by using different strategies such as the PID controller, Bang-Bang controller, Neural network controller, and Fuzzy controller, to adjust the length of the (SCPMA) between 30 cm and 24 cm by utilizing the amount of air coming from the air compressor. All of these strategies will be theoretically implemented using the MATLAB/Simulink package. Also, the performance of these control systems will be compared with respect to the time-domain characteristics and the root mean square error (RMSE). As a result, the controller performance accuracy and robustness ranged from one controller to another, and we found that the fuzzy logic controller was one of the best strategies used here according to the simplicity of the implementation and the very accurate response obtained from this method.
This paper presents a method for improving the speed profile of a three phase induction motor in direct torque control (DTC) drive system using a proposed fuzzy logic based speed controller. A complete simulation of the conventional DTC and closed-loop for speed control of three phase induction motor was tested using well known Matlab/Simulink software package. The speed control of the induction motor is done by using the conventional proportional integral (PI) controller and the proposed fuzzy logic based controller. The proposed fuzzy logic controller has a nature of (PI) to determine the torque reference for the motor. The dynamic response has been clearly tested for both conventional and the proposed fuzzy logic based speed controllers. The simulation results showed a better dynamic performance of the induction motor when using the proposed fuzzy logic based speed controller compared with the conventional type with a fixed (PI) controller.
Soft robotics is a modern technique that allows robots to have more capabilities than conventional rigid robots. Pneumatic Muscle Actuators (PMAs), also known as McKibben actuators, are an example of soft actuators. This research covered the design and production of a pneumatic robot end effector. Smooth, elastic, flexible, and soft qualities materials have contributed to the creation of Soft Robot End-Effector (SREE). To give SREE compliance, it needs to handle delicate objects while allowing it to adapt to its surroundings safely. The research focuses on the variable stiffness SREE’s inspiration design, construction, and manufacturing. As a result, a new four-fingered variable stiffness soft robot end effector was created. SREE has been designed using two types of PMAs: Contractor PMAs (CPMAs) and Extensor PMAs (EPMAs). Through tendons and Contractor PMAs, fingers can close and open. SREE was tested and put into practice to handle various object types. The innovative movement of the suggested SREE allows it to grip with only two fingers and open and close its grasp with all of its fingers.
In recent years, there has been a considerable rise in the applications in which object or image categorization is beneficial for example, analyzing medicinal images, assisting persons to organize their collections of photos, recognizing what is around self-driving vehicles, and many more. These applications necessitate accurately labeled datasets, in their majority involve an extensive diversity in the types of images, from cats or dogs to roads, landscapes, and so forth. The fundamental aim of image categorization is to predict the category or class for the input image by specifying to which it belongs. For human beings, this is not a considerable thing, however, learning computers to perceive represents a hard issue that has become a broad area of research interest, and both computer vision techniques and deep learning algorithms have evolved. Conventional techniques utilize local descriptors for finding likeness between images, however, nowadays; progress in technology has provided the utilization of deep learning algorithms, especially the Convolutional Neural Networks (CNNs) to auto-extract representative image patterns and features for classification The fundamental aim of this paper is to inspect and explain how to utilize the algorithms and technologies of deep learning to accurately classify a dataset of images into their respective categories and keep model structure complication to a minimum. To achieve this aim, must focus precisely and accurately on categorizing the objects or images into their respective categories with excellent results. And, specify the best deep learning-based models in image processing and categorization. The developed CNN-based models have been proposed and a lot of pre-training models such as (VGG19, DenseNet201, ResNet152V2, MobileNetV2, and InceptionV3) have been presented, and all these models are trained on the Caltech-101 and Caltech-256 datasets. Extensive and comparative experiments were conducted on this dataset, and the obtained results demonstrate the effectiveness of the proposed models. The obtained results demonstrate the effectiveness of the proposed models. The accuracy for Caltech-101 and Caltech-256 datasets was (98.06% and 90%) respectively.
Fast and accurate frequency estimation is essential in various engineering applications, including control systems, communications, and resonance sensing systems. This study investigates the effect of sample size on the interpolation algorithm of frequency estimation. In order to enhance the accuracy of frequency estimation and performance, we describe a novel method that provides a number of approaches for calculating and defending the sample size for of the window function designs, whereas, the correct choice of the type and the size of the window function makes it possible to reduce the error. Computer simulation using Matlab / Simulink environment is performed to investigate the proposed procedure’s performance and feasibility. This study performs the comparison of the interpolation algorithm of frequency estimation strategies that can be applied to improve the accuracy of the frequency estimation. Simulation results shown that the proposed strategy with the Parzen and Flat-top gave remarkable change in the maximum error of frequency estimation. They perform better than the conventional windows at a sample size equal to 64 samples, where the maximum error of frequency estimation is 2.13e-2 , and 2.15e-2 for Parzen and Flat-top windows, respectively. Moreover, the efficiency and performance of the Nuttall window also perform better than other windows, where the maximum error is 7.76×10-5 at a sample size equal to 8192. The analysis of simulation result showed that when using the proposed strategy to improve the accuracy of the frequency estimation, it is first essential to evaluate what is the maximum number of samples that can be obtained, how many spectral lines should be used in the calculations, and only after that choose a suitable window.
Beam squint phenomenon is considered one of the most drawbacks that limit the use of (mm-waves) array antennas; which causes significant degradation in the BER of the system. In this paper, a uniform linear array (ULA) system is exemplified at millimeter (mm-waves) frequency bands to realize the effects of beam squint phenomena from different directions on an equivalent gain response to represent the channel performance in terms of bit error rate (BER). A simple QPSK passband signal model is developed and tested according to the proposed antenna array with beam squint. The computed results show that increasing the passband bandwidth and the number of antenna elements, have a significant degradation in BER at the receiver when the magnitude and phase errors caused by the beam squint at 26 GHz with various spectrum bandwidths.
Vehicle Ad-hoc Network (VANET) is a type of wireless network that enables communication between vehicles and Road Side Units (RSUs) to improve road safety, traffic efficiency, and service delivery. However, the widespread use of vehicular networks raises serious concerns about users’ privacy and security. Privacy in VANET refers to the protection of personal information and data exchanged between vehicles, RSUs, and other entities. Privacy issues in VANET include unauthorized access to location and speed information, driver and passenger identification, and vehicle tracking. To ensure privacy in VANET, various technologies such as pseudonymization, message authentication, and encryption are employed. When vehicles frequently change their identity to avoid tracking, message authentication ensures messages are received from trusted sources, and encryption is used to prevent unauthorized access to messages. Therefore, researchers have presented various schemes to improve and enhance the privacy efficiency of vehicle networks. This survey article provides an overview of privacy issues as well as an in-depth review of the current state-of-the-art pseudonym-changing tactics and methodologies proposed.
Rehabilitation robots have become one of the main technical instruments that Treat disorder patients in the biomedical engineering field. The robotic glove for the rehabilitation is basically made of specialized materials which can be designed to help the post-stroke patients. In this paper, a review of the different types of robotic glove for Rehabilitation have been discussed and summarized. This study reviews a different mechanical system of robotic gloves in previous years. The selected studies have been classified into four types according to the Mechanical Design: The first type is a tendon-driven robotic glove. The second type of robotic glove works with a soft actuator as a pneumatic which is operated by air pressure that passes through a plastic pipe, pressure valves, and air compressor. The third type is the exoskeleton robotic gloves this type consists of a wearable mechanical design that can used a finger-based sensor to measure grip strength or is used in interactive video applications. And the fourth type is the robotic glove with a liner actuator this type consists of a tape placed on the fingers and connected to linear actuators to open and close the fingers during the rehabilitation process.
This paper presents a comprehensive analysis of a new direct detection polarization shift keying (DD POLSK) receiver structure that is based on Jones matrix technique. The bit - error rate (BER) characteristics of the receiver is examined under system impairments and the results are compared with those related to other DD POLSK receivers reported in the literature. The results indicate that Jones matrix receiver is less sensitive to optical amplifier gain variation when compared with other receivers.
In this paper, a control strategy for a combination PV-BESS-SC hybrid system in islanded microgrid with a DC load is designed and analyzed using a new topology. Although Battery Energy Storage System (BESS) is employed to keep the DC bus voltage stable; however, it has a high energy density and a low power density. On the other hand, the Supercapacitor (SC) has a low energy density but a high-power density. As a result, combining a BESS and an SC is more efficient for power density and high energy. Integrating the many sources is more complicated. In order to integrate the SC and BESS and deliver continuous power to the load, a control strategy is required. A novel method for controlling the bus voltage and energy management will be proposed in this paper. The main advantage of the proposed system is that throughout the operation, the State of Charging (SOC), BESS current, and SC voltage and current are all kept within predetermined ranges. Additionally, SC balances fast- changing power surges, while BESS balances slow-changing power surges. Therefore, it enhances the life span and minimizes the current strains on BESS. To track the Maximum Power Point (MPP) or restrict power from the PV panel to the load, a unidirectional boost converter is utilized. Two buck converters coupled in parallel with a boost converter are proposed to charge the hybrid BESS-SC. Another two boost converters are used to manage the discharge operation of the BESS-SC storage in order to reduce losses. The simulation results show that the proposed control technique for rapid changes in load demand and PV generation is effective. In addition, the proposed technique control strategy is compared with a traditional control strategy.
Today, the trends are the robotics field since it is used in too many environments that are very important in human life. Covid 19 disease is now the deadliest disease in the world, and most studies are being conducted to find solutions and avoid contracting it. The proposed system senses the presence according to a specific injury to warn of it and transfer it to the specialist doctor. This system is designed to work in service departments such as universities, institutes, and all state departments serving citizens. This system consists of two parts: the first is fixed and placed on the desk and the other is mobile within a special robot that moves to perform the required task. This system was tested at the University of Basrah within the college of engineering, department of electrical Engineering, on teaching staff, students, and staff during the period of final academic exams. The presence of such a device is considered a warning according to a specific condition and isn’t a treatment for it, as the treatment is prescribed by the specialist doctor. It is found that the average number of infected cases is about 3% of the total number of students and the teaching staff and the working staff. The results were documented in special tables that go to the dean of the college with the attendance tables to know the daily health status of the students.
Competitive trend towards restructuring and unbundling of transmission services has resulted in the need renteto discover the impact of a particular generator to load. This paper initially presents the analysis of three diff reactive power valuation methods namely, Modified Y bus , Virtual flow approach and Modified Power flow tracing to compute the reactive power output from a particular generator to particular load. Among these methods, the modified power flow electricity tracing method is identified as the best because of its various features. Secondly, based on this Method, the opportunity cost for practical system is determined. Hence, this method can be useful in providing additional insight into power system operation and can be used to modify existing tariffs of charging for reactive power transmission loss and reactive power transmission services. Simulation and comparison results are shown by taking IEEE 30 bus system as test system.
This paper presents a comprehensive analysis for the performance of heterojunction bipolar phototransistor (HPT) as an essential element for optoelectronic switch configurations. The theory of operation of the (HPT) is reviewed. Analytical expressions are drived for transistor current components, optical gain $G_{opt}$ and DC current gain $h_{FE}$ in common emitter configuration. The analysis enables one to study the influence of various structure parameters and incident optical power on the optical gain characteristics of the (HPT). Simulation results are presented for a $1.3~\mu m$ $\text{In}_{0.53}\text{Ga}_{0.47}\text{As}/\text{InP}$ structure.
A compact and low cost butterfly shaped UWB filtenna with a pair of parasitic elements and a pair of slits is proposed in this work. The filtenna is supposed to be designed on a common and low-cost FR4 substrate with overall dimensions of 26mm*20mm*1.6mm .By inserting a pair of g /2( where g is waveguide wavelength ) D-shaped parasitic elements around the antenna feed line, the radiation of the 5 GHz WLAN applications is canceled to eliminated the interference . Furthermore, the rejection of the X-band satellite downlink is achieved by engraving a pair of g /4 J-shaped slits on the ground plane. The simulation results exhibits the perfect coverage of the proposed filtenna for the UWB frequency band as well as the elimination of the undesired radiation within the filtenna operating band.
Recently, Jones matrix parameter shift keying (JMPSK) technique has been proposed in the literature to achieve phase noise and polarization state insensitive optical communication systems. The aim of this paper is to examine the performance of this system in the presence of system impairments, namely channel dichroism. A comprehensive analysis is presented to assess the effect of dichroism on the bit-error-rate (BER) characteristics of JMPSK receiver.
Energy exchange between AC grid and DC supply that is a part of a hybrid electric micro-grid takes place using various power converter designs. The single-phase, single-stage, AC-DC power dual active bridge converter is one option. The phase-shift modulation is used to regulate energy flow in both directions. The topology of one stage AC-DC dual active bridge converter based in bidirectional switching modules has been introduced. This paper next introduces the analysis of the AC side current considering basic modulation functions and suggests an optimum phase-shifted modulation strategy. The proposed modulation function provides minimum harmonics distortion. A simulation study is presented to compare the proposed strategy to the basic sinusoidal and triangular modulation techniques. The results show that the modified modulation reduces the average THD by about 55% and 39% compared to the standard sinusoidal and triangular modulation strategies respectively and ensures linear relationship between the transferred power and magnitude control coefficient.
Hybrid electric vehicles have received considerable attention because of their ability to improve fuel consumption compared to conventional vehicles. In this paper, a series-parallel hybrid electric vehicle is used because they combine the advantages of the other two configurations. In this paper, the control unit for a series-parallel hybrid electric vehicle is implemented using a Nonlinear Model Predictive Control (NMPC) strategy. The NMPC strategy needs to create a vehicle energy management optimization problem, which consists of the cost function and its constraints. The cost function describes the required control objectives, which are to improve fuel consumption and obtain a good dynamic response to the required speed while maintaining a stable value of the state of charge (SOC) for batteries. While the cost function is subject to the physical constraints and the mathematical prediction model that evaluate vehicle's behavior based on the current vehicle measurements. The optimization problem is solved at each sampling step using the (SQP) algorithm to obtain the optimum operating points of the vehicle's energy converters, which are represented by the torque of the vehicle components.
In recent years, artificial intelligence techniques such as wavelet neural network have been applied to control the speed of the BLDC motor drive. The BLDC motor is a multivariable and nonlinear system due to variations in stator resistance and moment of inertia. Therefore, it is not easy to obtain a good performance by applying conventional PID controller. The Recurrent Wavelet Neural Network (RWNN) is proposed, in this paper, with PID controller in parallel to produce a modified controller called RWNN-PID controller, which combines the capability of the artificial neural networks for learning from the BLDC motor drive and the capability of wavelet decomposition for identification and control of dynamic system and also having the ability of self-learning and self-adapting. The proposed controller is applied for controlling the speed of BLDC motor which provides a better performance than using conventional controllers with a wide range of speed. The parameters of the proposed controller are optimized using Particle Swarm Optimization (PSO) algorithm. The BLDC motor drive with RWNN-PID controller through simulation results proves a better in the performance and stability compared with using conventional PID and classical WNN-PID controllers.
In this paper, a compact two-element cylindrical dielectric resonator antenna (CDRA) array with corporate feeding is proposed for X-band applications. The dielectric resonator antenna (DRA) array is excited by a microstrip feeder using an efficient aperture-coupled method. The designed array antenna is analyzed using a CST microwave studio. The fabricated sample of the proposed CDRA antenna array showed bandwidth extending from 10.42GHz to 12.84GHz (20.8%). The achieved array gain has a maximum of 9.29dB i at frequency of 10.7GHz. This is about 2.06dB i enhancement of the gain in comparison with a single pellet CDRA. The size of the whole antenna structure is about 50 50mm 2 .
The reliability and feasibility of optical coherent communication system are strongly conditioned by laser phase noise and fluctuations of the state of polarization (SOP) of the optical field at the output of conventional single mode fiber. The double frequency parameter shift keying (DFPSK) system has been proposed in the literature as an efficient scheme that allows compensation of both effects by sending a reference channel that is suitably frequency shifted by using polarization modulation. This paper presents a comprehensive theoretical analysis for the performance of this system in the presence of dichroism which is introduced when the transmission channel has polarization dependent losses or amplifications. The results indicate that the performance of DFPSK system is affected by dichroism even in the low noise frequency regime.
Efficient energy collection from photovoltaic (PV) systems in environments that change is still a challenge, especially when partial shading conditions (PSC) come into play. This research shows a new method called Maximum Power Point Tracking (MPPT) that uses fuzzy logic and neural networks to make PV systems more flexible and accurate when they are exposed to PSC. Our method uses a fuzzy logic controller (FLC) that is specifically made to deal with uncertainty and imprecision. This is different from other MPPT methods that have trouble with the nonlinearity and transient dynamics of PSC. At the same time, an artificial neural network (ANN) is taught to guess where the Global Maximum Power Point (GMPP) is most likely to be by looking at patterns of changes in irradiance and temperature from the past. The fuzzy controller fine-tunes the ANN’s prediction, ensuring robust and precise MPPT operation. We used MATLAB/Simulink to run a lot of simulations to make sure our proposed method would work. The results showed that combining fuzzy logic with neural networks is much better than using traditional MPPT algorithms in terms of speed, stability, and response to changing shading patterns. This innovative technique proposes a dual-layered control mechanism where the robustness of fuzzy logic and the predictive power of neural networks converge to form a resilient and efficient MPPT system, marking a significant advancement in PV technology.
Four-leg voltage source inverter is an evolution of the three-leg inverter, and was ought about by the need to handle the non-linear and unbalanced loads. In this work Matlab/ Simulink model is presented using space vector modulation technique. Simulation results for worst conditions of unbalanced linear and non-linear loads are obtained. Observation for the continuity of the fundamental inverter output voltages vector in stationary coordinate is detected for better performance. Matlab programs are executed in block functions to perform switching vector selection and space vector switching.
It's not easy to implement the mixed / optimal controller for high order system, since in the conventional mixed / optimal feedback the order of the controller is much than that of the plant. This difficulty had been solved by using the structured specified PID controller. The merit of PID controllers comes from its simple structure, and can meets the industry processes. Also it have some kind of robustness. Even that it's hard to PID to cope the complex control problems such as the uncertainty and the disturbance effects. The present ideas suggests combining some of model control theories with the PID controller to achieve the complicated control problems. One of these ideas is presented in this paper by tuning the PID parameters to achieve the mixed / optimal performance by using Intelligent Genetic Algorithm (IGA). A simple modification is added to IGA in this paper to speed up the optimization search process. Two MIMO example are used during investigation in this paper. Each one of them has different control problem.
Recently, there is increasing interest in using joint transform correlation (JTC) technique for optical pattern recognition. In this technique, the target and reference images are jointed together in the input plane and no matched filter is required. In this paper, the JTC is investigated using simulation technique. A new discrimination decision algorithm is proposed to recognize the correlation output for different object shapes (dissimilar shapes). Also, new architectures are proposed to overcome the main problems of the conventional JTC.
Analysis and performance predictions of optical frequency division multiplexing (OFDM) receivers incorporating semiconductor optical amplifier (SOA) demultiplexer are presented. The analysis takes into account the influence of finite laser linewidth and various noise sources associated with the optically preamplified detection system. The results indicate clearly that the normalized crosstalk level must be kept below 10.8 dB to prevent the occurrence of a bit-error-rate (BER) floor at a level greater than $10^{-9}$
In medium voltage and high-power drive applications, pulse width modulation (PWM) techniques are widely used to achieve effective speed control of AC motors. In real-time, an industrial drive system requires reduced hardware complexity and low computation time. The reliability of the AC drive can be improved with the FPGA (field programmable gate array) hardware equipped with digital controllers. To improve the performance of AC drives, a new FPGA-based Wavect real-time prototype controller (Xilinx ZYNQ-7000 SoC) is used to verify the effectiveness of the controller. These advanced controllers are capable of reducing computation time and enhancing the drive performance in real- time applications. The comparative performance analysis is carried out for the most commonly used voltage source inverter (VSI)-based PWM techniques such as sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM) for three-phase, two-level inverters. The comparative study shows the SVPWM technique utilizes DC bus voltage more effectively and produces less harmonic distortion in terms of higher output voltage, flexible control of output frequency, and reduced harmonic distortion at output voltage for motor control applications. The simulation and hardware results are verified and validated by using MATLAB/Simulink software and FPGA-based Wavect real-time controller respectively.
In recent years, wireless microrobots have gotten more attention due to their huge potential in the biomedical field, especially drug delivery. Microrobots have several benefits, including small size, low weight, sensitivity, and flexibility. These characteristics have led to microscale improvements in control systems and power delivery with the development of submillimeter-sized robots. Wireless control of individual mobile microrobots has been achieved using a variety of propulsion systems, and improving the actuation and navigation of microrobots will have a significant impact. On the other hand, actuation tools must be integrated and compatible with the human body to drive these untethered microrobots along predefined paths inside biological environments. This study investigated key microrobot components, including medical applications, actuation systems, control systems, and design schemes. The efficiency of a microrobot is impacted by many factors, including the material, structure, and environment of the microrobot. Furthermore, integrating a hybrid actuation system and multimodal imaging can increase the microrobot’s navigation effect, imaging algorithms, and working environment. In addition, taking into account the human body’s moving distance, autonomous actuating technology could be used to deliver microrobots precisely and quickly to a specific position using a combination of quick approaches.
This paper presents a simplified control method for three-phase active power filter by calculating the required reactive and harmonics current of the load. The active power filter needs this current to correct the power factor and eliminate the generated harmonics by nonlinear loads. This method has the advantages of using only one current sensor and effectiveness in achieving the required compensation characteristics. The proposed circuit may be operate at frequencies ranging from 40 to 60 Hz, and it also responds very fast under sudden changes in the load conditions. The considered system is analyzed and a prototype is also developed and tested to demonstrate the performance of the implemented active power filter in the power factor improvement and harmonics elimination. Finally, predicted results are verified experimentally.
This article analyzes thoroughly the performance of the Multi-Pulse Diode Rectifiers (MPDRs) regarding the quality of input/output voltage and currents. Two possible arrangements of MPDRs are investigated: series and parallel. The impact of the DC side connection on the performance of the MPDRs regarding the operation parameters and rectifier indices are comprehensively examined. Detailed analytical formulas are advised to identify clearly the key variables that control the operation of MPDRs. Moreover, comprehensive simulation results are presented to quantify the performance and validate the analytical analysis. Test-rig is set up to recognize the promising arrangement of MPDRs. Significant correlation is there between simulation and practical results. The analytical results are presented for aircraft systems (400Hz), and power grid systems (60Hz). This is to study the impact of voltage and frequency levels on the topology type of MPDRs. In general, each topology shows merits and have limitations.
Nowadays, multimedia communication has become very widespread and this requires it to be protected from attackers and transmitted securely for reliability. Encryption and decryption techniques are useful in providing effective security for speech signals to ensure that these signals are transmitted with secure data and prevent third parties or the public from reading private messages. Due to the rapid improvement in digital communications over the recent period up to the present, the security of voice data transmitted over various networks has been classified as a favored field of study in earlier years. The contributions to audio encryption are discussed in this review. This Comprehensive review mainly focuses on presenting several kinds of methods for audio encryption and decryption the analysis of these methods with their advantages and disadvantages have been investigated thoroughly. It will be classified into encryption based on traditional methods and encryption based on advanced chaotic systems. They are divided into two types, continuous-time system, and discrete-time system, and also classified based on the synchronization method and the implementation method. In the fields of information and communications security, system designers face many challenges in both cost, performance, and architecture design, Field Programmable gate arrays (FPGAs) provide an excellent balance between computational power and processing flexibility. In addition, encryption methods will be classified based on Chaos-based Pseudo Random Bit Generator, Fractional-order systems, and hybrid chaotic generator systems, which is an advantageous point for this review compared with previous ones. Audio algorithms are presented, discussed, and compared, highlighting important advantages and disadvantages. Audio signals have a large volume and a strong correlation between data samples. Therefore, if traditional cryptography systems are used to encrypt such huge data, they gain significant overhead. Standard symmetric encryption systems also have a small key-space, which makes them vulnerable to attacks. On the other hand, encryption by asymmetric algorithms is not ideal due to low processing speed and complexity. Therefore, great importance has been given to using chaotic theory to encode audio files. Therefore, when proposing an appropriate encryption method to ensure a high degree of security, the key space, which is the critical part of every encryption system, and the key sensitivity must be taken into account. The key sensitivity is related to the initial values and control variables of the chaotic system chosen as the audio encryption algorithm. In addition, the proposed algorithm should eliminate the problems of periodic windows, such as limited chaotic range and non-uniform distribution, and the quality of the recovered audio signal remains good, which confirms the convenience, reliability, and high security.
In order to provide an efficient, low cost, and small size radiating structure that passes a certain frequency band with negligible amount of interference, the combination of filters and antennas is proposed to form a single element called filtenna. This paper presents a filtenna element with compact size that can radiates in the 5G mid-band frequency range (3.6-3.8 GHz) and perfectly rejects all the frequencies outside this range. The filtenna is composed of a printed circuit antenna that is terminated with a crescent shaped stub that is coupled electromagnetically with a miniaturized sharp band-pass filter. The simulation results show a filtenna reflection coefficient with a reduced value within the intended 5G band and with high values along the other unwanted frequencies. Moreover, the structure has an omnidirectional pattern with reasonable gain value within the band of interest, and this makes the antenna very suitable for portable 5G devices.
Soft-switching technique can substantially improve the performance of power converters, mainly due to the increase of switching frequency, that result in better modulation quality. This is more concerned particularly in the high power applications, where devices [gate turn off (GTO) or something else similar) can not operate over a few hundreds of hertz in conventional hard switching converter structures. In this paper, design and analysis of moderate power ZCT three-phase PWM inverter has been presented. Also, the designed inverter and its novel control circuit is implemented experimentally to investigate its characteristics with this new zero-current transition ZCT technique.
Precise power sharing considered is necessary for the effective operation of an Autonomous microgrid with droop controller especially when the total loads change periodically. In this paper, reactive power sharing control strategy that employs central controller is proposed to enhance the accuracy of fundamental reactive power sharing in an islanded microgrid. Microgrid central controller is used as external loop requiring communications to facilitate the tuning of the output voltage of the inverter to achieve equal reactive power sharing dependent on reactive power load to control when the mismatch in voltage drops through the feeders. Even if central controller is disrupted the control strategy will still operate with conventional droop control method. additionally, based on the proposed strategy the reactive power sharing accuracy is immune to the time delay in the central controller. The developed of the proposed strategy are validated using simulation with detailed switching models in PSCAD/EMTDC.
In this paper the dynamic behavior of linear induction motor is described by a mathematical model taking into account the end effects and the core losses. The need for such a model rises due to the complexity of linear induction motors electromagnetic field theory. The end affects are modeled by introducing a speed dependent scale factor to the magnetizing inductance and series resistance in the d-axis equivalent circuit. Simulation results are presented to show the validity of the model during both no-load and sudden load change intervals. This model can also be used directly in simulation researches for linear induction motor vector control drive systems.
Audio encryption has gained popularity in a variety of fields including education, banking over the phone, military, and private audio conferences. Data encryption algorithms are necessary for processing and sending sensitive information in the context of secure speech conversations. In recent years, the importance of security in any communications system has increased. To transfer data securely, a variety of methods have been used. Chaotic system-based encryption is one of the most significant encryption methods used in the field of security. Chaos-based communication is a promising application of chaos theory and nonlinear dynamics. In this research, a chaotic algorithm for the new chaotic chameleon system was proposed, studied, and implemented. The chameleon chaotic system has been preferred to be employed because it has the property of changing from self-excited (SA) to hidden-attractor (HA) which increases the complexity of the system dynamics and gives strength to the encryption algorithm. A chaotic chameleon system is one in which, depending on the parameter values, the chaotic attractor alternates between being a hidden attractor and a self-excited attractor. This is an important feature, so it is preferable to use it in cryptography compared to other types of chaotic systems. This model was first implemented using a Field Programmable Gate Array (FPGA), which is the first time it has been implemented in practical applications. The chameleon system model was implemented using MATLAB Simulink and the Xilinx System Generator model. Self-excited, hidden, and coexisting attractors are shown in the proposed system. Vivado software was used to validate the designs, and Xilinx ZedBoard Zynq-7000 FPGA was used to implement them. The dynamic behavior of the proposed chaotic system was also studied and analysis methods, including phase portrait, bifurcation diagrams, and Lyapunov exponents. Assessing the quality of the suggested method by doing analyses of many quality measures, including correlation, differential signal-to-noise ratio (SNR), entropy, histogram analysis, and spectral density plot. The numerical analyses and simulation results demonstrate how well the suggested method performs in terms of security against different types of cryptographic assaults.
In this paper, a new method based on the combination of the Teaching-learning-based-optimization (TLBO) and Black-hole (BH) algorithm has been proposed for the reconfiguration of distribution networks in order to reduce active power losses and improve voltage profile in the presence of distributed generation sources. The proposed method is applied to the IEEE 33-bus radial distribution system. The results show that the proposed method can be a very promising potential method for solving the reconfiguration problem in distribution systems and has a significant effect on loss reduction and voltage profile improvement.
The necessity for an efficient algorithm for resource allocation is highly urgent because of increased demand for utilizing the available spectrum of the wireless communication systems. This paper proposes an Enhanced Bundle-based Particle Collision Algorithm (EB-PCA) to get the optimal or near optimal values. It applied to the Orthogonal Frequency Division Multiple Access (OFDMA) to evaluate allocations for the power and subcarrier. The analyses take into consideration the power, subcarrier allocations constrain, channel and noise distributions, as well as the distance between user's equipment and the base station. Four main cases are simulated and analyzed under specific operation scenarios to meet the standard specifications of different advanced communication systems. The sum rate results are compared to that achieved with employing another exist algorithm, Bat Pack Algorithm (BPA). The achieved results show that the proposed EB-PAC for OFDMA system is an efficient algorithm in terms of estimating the optimal or near optimal values for both subcarrier and power allocation.
This article presents a novel optimization algorithm inspired by camel traveling behavior that called Camel algorithm (CA). Camel is one of the extraordinary animals with many distinguish characters that allow it to withstand the severer desert environment. The Camel algorithm used to find the optimal solution for several different benchmark test functions. The results of CA and the results of GA and PSO algorithms are experimentally compared. The results indicate that the promising search ability of camel algorithm is useful, produce good results and outperform the others for different test functions.
This paper suggests the use of the traditional parallel resonant dc link (PRDCL) circuit to give soft switching to the Four-leg Space Vector Pulse Width Modulation (SVPWM) inverter. The proposed circuit provides a short period of zero voltage across the inverter during the zero-vectors occurrence. The transition between the zero and active vectors accomplished with zero- voltage condition (ZVC), this reduces the switching losses. Moreover, the inverter output voltage Total Harmonic Distortion (THD) not affected by circuit operation, since the zero voltage periods occur simultaneously with zero-vector periods. To confirm the results, balanced and unbalanced loads are used. Matlab/Simulink model implemented for simulation.
This study proposes a blind speech separation algorithm that employs a single-channel technique. The algorithm’s input signal is a segment of a mixture of speech for two speakers. At first, filter bank analysis transforms the input from time to time-frequency domain (spectrogram). Number of sub-bands for the filter is 257. Non-Negative Matrix Factorization (NNMF) factorizes each sub-band output into 28 sub-signals. A binary mask separates each sub-signal into two groups; one group belongs to the first speaker and the other to the second speaker. The binary mask separates each sub-signal of the (257×28) 7196 sub-speech signals. That separation cannot identify the speaker. Identification of the sub-signal speaker for each sub-signal is achieved by speaker clustering algorithms. Since speaker clustering cannot process without speaker segmentation, the standard windowed-overlap frames have been used to partition the speech. The speaker clustering process fetches the extracted phase angle from the spectrogram (of the mixture speech) and merges it into the spectrogram (of the recovered speech). Filter bank synthesizes these signals to produce a full-band speech signal for each speaker. Subjective tests denote that the algorithm results are accepted. Objectively, the researchers experimented with 66 mixture chats (6 females and 6 males) to test the algorithm. The average of the SIR test is 11.1 dB, SDR is 1.7 dB, and SAR is 2.8 dB.
The aim of this paper is to investigate the switching characteristics of hetrojunction phototransistor (HPT). First, the static characteristics of the HPT are given under ideal conditions to get a physical insight on the main parameters affecting it's response. Then the speed of response of HPT is addressed and supported by simulation results reported for $1.3~\mu m$ InGaAs/InP transistor.
In this paper, a new algorithm called the virtual circle tangents is introduced for mobile robot navigation in an environment with polygonal shape obstacles. The algorithm relies on representing the polygonal shape obstacles by virtual circles, and then all the possible trajectories from source to target is constructed by computing the visible tangents between the robot and the virtual circle obstacles. A new method for searching the shortest path from source to target is suggested. Two states of the simulation are suggested, the first one is the off-line state and the other is the on-line state. The introduced method is compared with two other algorithms to study its performance.
In this paper, a new algorithm called table-based matching for multi-robot (node) that used for localization and orientation are suggested. The environment is provided with two distance sensors fixed on two beacons at the bottom corners of the frame. These beacons have the ability to scan the environment and estimate the location and orientation of the visible nodes and save the result in matrices which are used later to construct a visible node table. This table is used for matching with visible-robot table which is constructed from the result of each robot scanning to its neighbors with a distance sensor that rotates at 360⁰; at this point, the location and identity of all visible nodes are known. The localization and orientation of invisible robots rely on the matching of other tables obtained from the information of visible robots. Several simulations implementation are experienced on a different number of nodes to submit the performance of this introduced algorithm.
In this article, a PD-type iterative learning control algorithm (ILC) is proposed to a nonlinear time-varying system for cases of measurement disturbances and the initial state errors. The proposed control approach uses a simple structure and has an easy implementation. The iterative learning controller was utilized to control a constant current source inverter (CSI) with pulse width modulation (PWM); subsequently the output current trajectory converged the sinusoidal reference signal and provided constant switching frequency. The learning controller's parameters were tuned using particle swarm optimization approach to get best optimal control for the system output. The tracking error limit is achieved using the convergence exploration. The proposed learning control scheme was robust against the error in initial conditions and disturbances which outcome from the system modeling inaccuracies and uncertainties. It could correct the distortion of the inverter output current waveform with less computation and less complexity. The proposed algorithm was proved mathematically and through computer simulation. The proposed optimal learning method demonstrated good performances.
The conventional multilevel inverter (MLI) is divided into three types: diode clamped MLI, cascade H Bridge MLI and flying capacitor MLI. The main disadvantage of these types is the higher required number of components when the number of the levels increases and this results in more switching losses, system higher cost, more complex of control circuit as well as less accuracy. The work in this paper proposes two topologies of nonconventional diode clamping MLI three phase nine levels and eleven levels. The first proposed topology has ten switches and six diodes per phase while the second topology has nine switches and four diodes per phase. The pulse width modulation (PWM) control method is used as a control to gate switches. THD of the two proposed topologies are analyzed and calculated according different values of Modulation index (where the power loss and efficiency are obtained and plotted.
The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communicating with the outside world. This article examines the use of the SVM, k-NN, and decision tree algorithms to classify EEG signals. To minimize the complexity of the data, maximum overlap discrete wavelet transform (MODWT) is used to extract EEG features. The mean inside each window sample is calculated using the Sliding Window Technique. The vector machine (SVM), k-Nearest Neighbor, and optimize decision tree load the feature vectors.
A single phase boost rectifier circuit is studied with and without feedforward techniques. The circuit is implemented and tested experimentally. It can be operated at high power factor (greater than 0.99), and at line current total harmonic distortion (THD) (less than 0.06), by selecting a suitable control parameters at the desired output power.
In this paper the identification and control for the impressed current cathodic protection (ICCP) system are present. Firstly, an identification model using an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) was implemented. The identification model consists of four inputs which are the aeration flow rates, the temperature, conductivity, and protection current, and one output that represented by the structure-to-electrolyte potential. The used data taken from an experimental CP system model, type impressed current submerged sample pipe carbon steel. Secondly, two control techniques are used. The first control technique use a conventional Proportional-Integral-Derivative (PID) controller, while the second is the fuzzy controller. The PID controller can be applied to control ICCP system and quite easy to implement. But, it required very fine tuning of its parameters based on the desired value. Furthermore, it needed time response more than fuzzy controller to track reference voltage. So the fuzzy controller has a faster and better response.
In this article, a novel three dimensional chaotic systems is presented. An extensive analysis including Lyapunov exponents, dissipation, symmetry, rest points with their properties is introduced. An adaptive tracking control system for the proposed chaos system has been designed. Also, synchronization system for two identical systems has been designed. The simulation results showed the effectiveness of the designed tracking and synchronization control systems.
The unprogrammed penetration for the loads in the distribution networks make it work in an unbalancing situation that leads to unstable operation for those networks. the instability coming from the imbalance can cause many serious problems like the inefficient use of the feeders and the heat increased in the distribution transformers. The demands response can be regarded as a modern solution for the problem by offering a program to decreasing the consumption behavior for the program's participators in exchange for financial incentives in specific studied duration according to a direct order from the utility. The paper uses a new suggested algorithm to satisfy the direct load control demand response strategy that can be used in solving the unbalancing problem in distribution networks. The algorithm procedure has been simulated in MATLAB 2018 to real data collected from the smart meters that have been installed recently in Baghdad. The simulation results of applying the proposed algorithm on different cases of unbalancing showed that it is efficient in curing the unbalancing issue based on using the demand response strategy.
Obstacle avoidance in mobile robot path planning represents an exciting field of robotics systems. There are numerous algorithms available, each with its own set of features. In this paper a Witch of Agnesi curve algorithm is proposed to prevent a collision by the mobile robot’s orientation beyond the obstacles which represents an important problem in path planning, further, to achieve a minimum arrival time by following the shortest path which leads to minimizing power loss. The proposed approach considers the mobile robot’s platform equipped with the LIDAR 360o sensor to detect obstacle positions in any environment of the mobile robot. Obstacles detected in the sensing range of the mobile robot are dealt with by using the Witch of Agnesi curve algorithm, this establishes the obstacle’s apparent vertices’ virtual minimum bounding circle with minimum error. Several Scenarios are implemented and considered based on the identification of obstacles in the mobile robot environment. The proposed system has been simulated by the V-REP platform by designing several scenarios that emulate the behavior of the robot during the path planning model. The simulation and experimental results show the optimal performance of the mobile robot during navigation is obtained as compared to the other methods with minimum power loss and also with minimum error. It’s given 96.3 percent in terms of the average of the total path while the Bezier algorithm gave 94.67 percent. While in experimental results the proposed algorithm gave 93.45 and the Bezier algorithm gave 92.19 percent.
In light of the widespread usage of power electronics devices, power quality (PQ) has become an increasingly essential factor. Due to nonlinear characteristics, the power electronic devices produce harmonics and consume lag current from the utility. The UPQC is a device that compensates for harmonics and reactive power while also reducing problems related to voltage and current. In this work, a three-phase, three-wire UPQC is suggested to reduce voltage-sag, voltage-swell, voltage and current harmonics. The UPQC is composed of shunt and series Active Power Filters (APFs) that are controlled utilizing the Unit Vector Template Generation (UVTG) technique. Under nonlinear loads, the suggested UPQC system can be improved PQ at the point of common coupling (PCC) in power distribution networks. The simulation results show that UPQC reduces the effect of supply voltage changes and harmonic currents on the power line under nonlinear loads, where the Total Harmonic Distortion (THD) of load voltages and source currents obtained are less than 5%, according to the IEEE-519 standard.
As a key type of mobile robot, the two-wheel mobile robot has been developed rapidly for varied domestic, health, and industrial applications due to human-like movement and balancing characteristics based on the inverted pendulum theory. This paper presents a developed Two-Wheel Self-Balanced Robot (TWSBR) model under road disturbance effects and simulated using MATLAB Simscape Multibody. The considered physical-mechanical structure of the proposed TWSBS is connected with a Simulink controller scheme by employing physical signal converters to describe the system dynamics efficiently. Through the Simscape environment, the TWSBR motion is visualized and effectively analyzed without the need for complicated analysis of the associated mathematical model. Besides, 3D visualization of real-time behavior for the implemented TWSBR plant model is displayed by Simulink Mechanics Explorer. Robot balancing and stability are achieved by utilizing Proportional Integral Derivative (PID) and Linear Quadratic Regulator (LQR) controllers' approaches considering specific control targets. A comparative study and evaluation of both controllers are conducted to verify the robustness and road disturbance rejection. The realized performance and robustness of developed controllers are observed by varying object-carrying loaded up on mechanical structure layers during robot motion. In particular, the objective weight is loaded on the robot layers (top, middle, and bottom) during disturbance situations. The achieved findings may have the potential to extend the deployment of using TWSBRs in the varied important application.
The brain tumors are among the common deadly illness that requires early, reliable detection techniques, current identification, and imaging methods that depend on the decisions of neuro-specialists and radiologists who can make possible human error. This takes time to manually identify a brain tumor. This work aims to design an intelligent model capable of diagnosing and predicting the severity of magnetic resonance imaging (MRI) brain tumors to make an accurate decision. The main contribution is achieved by adopting a new multiclass classifier approach based on a collected real database with new proposed features that reflect the precise situation of the disease. In this work, two artificial neural networks (ANNs) methods namely, Feed Forward Back Propagation neural network (FFBPNN) and support vector machine (SVM), used to expectations the level of brain tumors. The results show that the prediction result by the (FFBPN) network will be better than the other method in time record to reach an automatic classification with classification accuracy was 97% for 3-class which is considered excellent accuracy. The software simulation and results of this work have been implemented via MATLAB (R2012b).
The drastic increase of residential load consumption in recent years result in over loading feeder lines and transformers for the Iraqi northern area distribution system especially in the city of Mosul. Solution for this problem require up to date research consumers load study to find the proper solution to stop excess overload in the transformers and the feeders. This paper include the regional survey for samples of consumers representing typical types of different standard of living and energy consumption by distributing questioners contain list of information such as load type in daily use. Also current readings are recorded for the individual consumer for the months of the year 2006. In addition to those readings, energy consumption is recorded once every two months. The registered readings are used in conjunction with the list of questionnaires to find a sample (for different loads) that coincide with the list of questionnaires for current and energy readings. Resulting in the feasibility of using the sample to know the peak value of current for any consumer even if he is not included in the list of questionnaires and for any new consumer, since it become possible to decide the size of the transformers and feeder lines, to overcome the problem of overloading in any part of the distribution system. The Artificial Neural Network (ANN) is used in this paper to find the above mentioned sample.
In this paper, a model of PM DC Motor Drive is presented. The nonlinear dynamics of PM DC Motor Drive is discussed. The drive system shows different dynamical behaviors; periodic, quasi-period, and chaotic and are characterized by bifurcation diagrams, time series evolution, and phase portrait. The stabilization of chaos to a fixed point is adopted using slide mode controller (SMC). The chaotic dynamics are suppressed and the fixed point dynamics are observed after the activation of proposed controller. Numerical simulation results show the effectiveness of the proposed method of control for stabilization the chaos and different disturbances in the system.
This paper presents the design of a path planning system in an environment that contains a set of static and dynamic polygon obstacles localized randomly. In this paper, an algorithm so-called (Polygon shape tangents algorithm) is proposed to move a mobile robot from a source point to a destination point with no collision with surrounding obstacles using the visibility binary tree algorithm. The methodology of this algorithm is based on predicting the steps of a robot trajectory from the source to the destination point. The polygon shapes tangent algorithm is compared with the virtual circles' tangents algorithm for different numbers of static and dynamic polygon obstacles for the time of arrival and the length of the path to the target. The obtained result shows that the used algorithm has better performance than the other algorithms and gets less time of arrival and shortest path with free collision.