This work proposes an optimization algorithm to control speed of a permanent magnet synchronous motor (PMSM) during starting and speed reversal of motor, as well as during load disturbance conditions. The objective is to minimize the integral absolute control error of the PMSM shaft speed to achieve fast and accurate speed response under load disturbance and speed reversal conditions. The maximum overshoot, peak time, settling time and rise time of the motor is also minimized to obtain efficient transient speed response. Optimum speed control of PMSM is obtained with the aid of a PID speed controller. Modified Particle Swarm Optimization (MPSO) and Ant Colony Optimization (ACO) techniques has been employed for tuning of the PID speed controller, to determine its gain coefficients (proportional, integral and derivative). Simulation results demonstrate that with use of MPSO and ACO techniques improved control performance of PMSM can be achieved in comparison to the classical Ziegler-Nichols (Z-N) method of PID tuning.
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...ijscmcjournal
This paper presents a new approach to determine the optimal proportional-integral-derivative controller
parameters for the speed control of a separately excited DC motor using firefly optimization technique.
Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in
nature. The firefly optimization technique is successfully implemented using MATLAB software. A
comparison is drawn from the results obtained between the linear quadratic regulator and firefly
optimization techniques. Simulation results are presented to illustrate the performance and validity of the
design method.
An Optimal LFC in Two-Area Power Systems Using a Meta-heuristic Optimization...IJECEIAES
In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. This metaheuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters (퐾 ) automatically. The developed controller (HSPI) with LFC loop is very important to minimize the system frequency and 푝 , 퐾 푖 keep the system power is maintained at scheduled values under sudden loads changes. Integral absolute error (IAE) is used as an objective function to enhance the overall system performance in terms of settling time, maximum deviation, and peak time. The two-area power systems and developed controller are modelled using MATLAB software (Simulink/Code). As a result, the developed control algorithm (HS-PI) is more robustness and efficient as compared to PSO-PI control algorithm under same operation conditions.
An Adaptive Internal Model for Load Frequency Control using Extreme Learning ...TELKOMNIKA JOURNAL
As an important part of a power system, a load frequency control has to be prepared with a better controller to ensure internal frequency stability. In this paper, an Internal Model Control (IMC) scheme for a Load Frequency Control (LFC) with an adaptive internal model is proposed. The effectiveness of the IMC control has been tested in a three area power system. Results of the simulation show that the proposed IMC with Extreme Learning Machine (ELM) based adaptive model can accurately cover the power system dynamics. Furthermore, the proposed controller can effectively reduce the frequency and mechanical power deviation under disturbances of the power system.
Design of GCSC Stabilizing Controller for Damping Low Frequency OscillationsIJAEMSJORNAL
This paper presents a systematic procedure for modeling and simulation of a power system equipped with FACTS type Gate Controlled Series Compensator (GCSC) based stabilizer controller. Single Machine Infinite Bus (SMIB) power system was investigated for evaluation of GCSC stabilizing controller for enhancing the overall dynamic system performance. PSO algorithm is employed to compute the optimal parameters of damping controller. Eigenvalues of system under various operating condition and nonlinear time domain simulation is employed to verify the effectiveness and robustness of GCSC stabilizing controller in damping low frequency oscillations (LFO) modes.
Permanent magnet direct current motors (PMDCM) are widely used in various applications such as space technologies, personal computers, medical, military, robotics, electrical vehicles, etc. In this paper, the mathematical model of PMDCM is designed and simulated using MATLAB software. The PMDCM speed is controlled using rate feedback controller due to its ability of improving system damping. To improve the controller performance, it’s parameters are tuned using genetic algorithm (GA) and direct search (DS) techniques. The tuning process based on different performance criteria. The most four common performance criteria used in this paper are JIAE (Integral of Absolute Error), JISE (Integral of Square Error), JITAE (Integral of Time-Weighted Absolute Error), and JITSE (Integral of Time-Weighted Square Error). The results obtained from these evolutionary techniques are compared. The results show an obvious improvement in system performance including enhancing the transient and steady state of PMDCM speed responses for all performance criteria.
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...ijscmcjournal
This paper presents a new approach to determine the optimal proportional-integral-derivative controller
parameters for the speed control of a separately excited DC motor using firefly optimization technique.
Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in
nature. The firefly optimization technique is successfully implemented using MATLAB software. A
comparison is drawn from the results obtained between the linear quadratic regulator and firefly
optimization techniques. Simulation results are presented to illustrate the performance and validity of the
design method.
An Optimal LFC in Two-Area Power Systems Using a Meta-heuristic Optimization...IJECEIAES
In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. This metaheuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters (퐾 ) automatically. The developed controller (HSPI) with LFC loop is very important to minimize the system frequency and 푝 , 퐾 푖 keep the system power is maintained at scheduled values under sudden loads changes. Integral absolute error (IAE) is used as an objective function to enhance the overall system performance in terms of settling time, maximum deviation, and peak time. The two-area power systems and developed controller are modelled using MATLAB software (Simulink/Code). As a result, the developed control algorithm (HS-PI) is more robustness and efficient as compared to PSO-PI control algorithm under same operation conditions.
An Adaptive Internal Model for Load Frequency Control using Extreme Learning ...TELKOMNIKA JOURNAL
As an important part of a power system, a load frequency control has to be prepared with a better controller to ensure internal frequency stability. In this paper, an Internal Model Control (IMC) scheme for a Load Frequency Control (LFC) with an adaptive internal model is proposed. The effectiveness of the IMC control has been tested in a three area power system. Results of the simulation show that the proposed IMC with Extreme Learning Machine (ELM) based adaptive model can accurately cover the power system dynamics. Furthermore, the proposed controller can effectively reduce the frequency and mechanical power deviation under disturbances of the power system.
Design of GCSC Stabilizing Controller for Damping Low Frequency OscillationsIJAEMSJORNAL
This paper presents a systematic procedure for modeling and simulation of a power system equipped with FACTS type Gate Controlled Series Compensator (GCSC) based stabilizer controller. Single Machine Infinite Bus (SMIB) power system was investigated for evaluation of GCSC stabilizing controller for enhancing the overall dynamic system performance. PSO algorithm is employed to compute the optimal parameters of damping controller. Eigenvalues of system under various operating condition and nonlinear time domain simulation is employed to verify the effectiveness and robustness of GCSC stabilizing controller in damping low frequency oscillations (LFO) modes.
Permanent magnet direct current motors (PMDCM) are widely used in various applications such as space technologies, personal computers, medical, military, robotics, electrical vehicles, etc. In this paper, the mathematical model of PMDCM is designed and simulated using MATLAB software. The PMDCM speed is controlled using rate feedback controller due to its ability of improving system damping. To improve the controller performance, it’s parameters are tuned using genetic algorithm (GA) and direct search (DS) techniques. The tuning process based on different performance criteria. The most four common performance criteria used in this paper are JIAE (Integral of Absolute Error), JISE (Integral of Square Error), JITAE (Integral of Time-Weighted Absolute Error), and JITSE (Integral of Time-Weighted Square Error). The results obtained from these evolutionary techniques are compared. The results show an obvious improvement in system performance including enhancing the transient and steady state of PMDCM speed responses for all performance criteria.
Hysteresis controllers (HC) are used to limit the torque and flux in the control band in conventional configuration of direct torque control (DTC) while in the space vector pulse width modulated (SVPWM) DTC, the HC are switched to PI or PID controllers. This paper presents a modern approach for the speed control applied on a DTC of a permanent magnet synchronous motor (PMSM) using the Cuckoo Search Optimization (CSO) algorithm in order to optimize the PI speed controller parameters of the outer loop and PID flux and torque controllers of the inner loop. The system is tested at no load and with a step change in load. The performance of the controllers is presented and the results of simulation indicate a very rapid dynamic response and the system achieves the steady state (SS.) in a very short time. Also it shows that both the SS. and dynamic performances are improved by applying of the CSO algorithm. The proposed DTC simulation model of the PMSM is presented using MATLAB / SIMULINK and capable of simulating both the steady-state and dynamic response. The CSO results are compared with another control strategy that incorporates fuzzy logic controller (FLC) with DTC.
Meta-heuristic optimization techniques are important tools to define the optimal solutions for many problems. In this paper, a new advanced artificial intelligence (AI) based direct torque control (DTC) speed drives are optimally designed and implemented in real time to achieve a high performance permanent-magnet synchronous-motor (PMSM) drive. Grey wolf (GW) algorithms are used with the standard PID-based DTC (PIDDTC) and with the DTC with fuzzy logic (FDTC) based speed controllers. DSPACE DS1202 is utilized in the real-time implementation. MATLAB SIMULINK is used to simulate the steady-state (S.S.) and dynamic responses. The overall system is tested at different operating conditions for both simulation and practical work and all results are presented. A comparison between experimental and simulation results is performed and also a comparison between different applied intelligent techniques is introduced.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Comparative Study of GA tuned and PSO tuned PI Controller Based Speed Contr...paperpublications3
Abstract: This paper presents a comparative study of Generic Algorithm (GA) and Partical Swarm Optimization (PSO) technique for determining the optimal parameters of (PI) controller for speed control of a brushless DC motor (BLDC) where the (BLDC) motor is modeled in simulink in MATLAB. The proposed technique was more efficient in improving the step response characteristics as well as reducing the steady-state error, rise time, settling time and maximum overshoot.
Metaheuristics-based Optimal Reactive Power Management in Offshore Wind Farms...Aimilia-Myrsini Theologi
The aim of the thesis is to optimally coordinate the reactive power sources in offshore wind farms in a predictive manner based to the principle of minimizing the wind farm power losses, as well the variations of the transformers tap positions. First, an accurate Neural Network-based wind speed forecasting algorithm was developed in order to counteract the uncertainty of the wind and finally, the optimal management of the available reactive sources is tackled by a metaheuristics-based method. Two different cases were investigated: a far-offshore wind farm with HVDC interconnection link and the AC connected Dutch wind farm BORSSELE.
Design and optimization of pid controller using genetic algorithmeSAT Journals
Abstract Natural evolution is mimicked by Genetic Algorithms (GAs) which is a stochastic global search method used for optimization. . In missile control systems Proportional Integral Derivative (PID) control is widely used, but due to empirically selected parameters Kp, Ki, Kd it is difficult to achieve parameter optimization. Genetic algorithm is a search algorithm that is based on natural selection and genetics principles.GA is a computational algorithm which deals with genetics of the human body. It evolves with the number of iterations. After ever iteration a better result is expected. These results are checked for the error. The fittest roots or solution are considered for the next generation based on the selection criterion. GA randomly generates the initial population of the PID control parameters according to the calculation of selection (Normalized Geometric Selection), crossover (Arithmetic Crossover) and mutation (Uniform Mutation), thus optimizing the control parameters. Mean Square Error (MSE) value is chosen as the performance assessment index. For a missile altitude control Proportional Integral Derivative (PID) controller using genetic algorithm is implemented & compared with the classical method Zeigler-Nichols (Z-N) in the paper. Z-N method is classical method which tunes the parameters of PID. The parameters of PID are difficult to tune. Tuned parameters give the optimum solution. Optimum solution generally converges to a solution having minimum error. Minimum error gives a response of the system in terms of maximum over shoot, Settling time, Rise time & Steady State Error. The designed PID with the Genetic Algorithm has much faster response than the classical method.
In this paper, the optimal control problem of a nonlinear robot manipulator in absence of holonomic constraint force based on the point of view of adaptive dynamic programming (ADP) is presented. To begin with, the manipulator was intervened by exact linearization. Then the framework of ADP and Robust Integral of the Sign of the Error (RISE) was developed. The ADP algorithm employs Neural Network technique to tune simultaneously the actor-critic network to approximate the control policy and the cost function, respectively. The convergence of weight as well as position tracking control problem was considered by theoretical analysis. Finally, the numerical example is considered to illustrate the effectiveness of proposed control design.
Priority based round robin (PBRR) CPU scheduling algorithmIJECEIAES
This paper introduce a new approach for scheduling algorithms which aim to improve real time operating system CPU performance. This new approach of CPU Scheduling algorithm is based on the combination of round-robin (RR) and Priority based (PB) scheduling algorithms. This solution maintains the advantage of simple round robin scheduling algorithm, which is reducing starvation and integrates the advantage of priority scheduling. The proposed algorithm implements the concept of time quantum and assigning as well priority index to the processes. Existing round robin CPU scheduling algorithm cannot be dedicated to real time operating system due to their large waiting time, large response time, large turnaround time and less throughput. This new algorithm improves all the drawbacks of round robin CPU scheduling algorithm. In addition, this paper presents analysis comparing proposed algorithm with existing round robin scheduling algorithm focusing on average waiting time and average turnaround time.
Fuzzy gain scheduling control apply to an RC Hovercraft IJECEIAES
The Fuzzy Gain Scheduling (FGS) methodology for tuning the ProportionalIntegral-Derivative (PID) traditional controller parameters by scheduling controlled gains in different phases, is a simple and effective application both in industries and real-time complex models while assuring the high achievements over pass decades, is proposed in this article. The Fuzzy logic rules of the triangular membership functions are exploited on-line to verify the Gain Scheduling of the Proportional-Integral-Derivative controller gains in different stages because it can minimize the tracking control error and utilize the Integral of Time Absolute Error (ITAE) minima criterion of the controller design process. For that reason, the controller design could tune the system model in the whole operation time to display the efficiency in tracking error. It is then implemented in a novel Remote Controlled (RC) Hovercraft motion models to demonstrate better control performance in comparison with the PID conventional controller.
Modeling and analysis of field-oriented control based permanent magnet synch...IJECEIAES
The permanent magnet synchronous motor (PMSM) acts as an electrical motor mainly used in many diverse applications. The controlling of the PMSM drive is necessary due to frequent usage in various systems. The conventional proportional-integral-derivative (PID) controller’s drawbacks are overcome with fuzzy logic controller (FLC) and adopted in the PMSM drive system. In this manuscript, an efficient field-oriented control (FOC) based PMSM drive system using a fuzzy logic controller (FLC) is modeled to improve the speed and torque response of the PMSM. The PMSM drive system is modeled using abc to αβ and αβ to abc transformation, 2-level space vector pulse width modulation (SVPWM), AC to DC rectifier with an inverter, followed by PMSM drive, proportional integral (PI) controller along with FLC. The FLC’s improved fuzzy rule set is adopted to provide faster speed response, less % overshoot time, and minimal steady-state error of the PMSM drive system. The simulation results of speed response, torque response, speed error, and phase currents are analyzed. The FLC-based PMSM drive is compared with the conventional PID-based PMSM drive system with better improvements in performance metrics.
Advanced Optimal PSO, Fuzzy and PI Controller with PMSM and WTGS at 5Hz Side ...IAES-IJPEDS
To use different control systems, like classical PI controller, Expert System
Fuzzy Logic Controller and optimization PSO controller. It used to control
for PMSM which worked in the integration system to Wind Energy. Wind
energy content of wind turbine, PMSM, rectifier, DC bus, inverter, filter,
load and grid. In the first step, to run the PMSM with different speeds to get
a different frequency to select the frequency on the side of a generation with
the rated speed. Second step, solve the mathematical equation to use different
values of wind speed with selected (15,20 m/s and less than with more than
15&20m/s). Third step, calculation the power generation with wind speed
(15 m/5 & 20 m/s). Fourth step, using these component system rectifier, DC
bus, inverter, filter, load & grid with WTGS & PMSM. Final step, uses
different control systems, like classical PI controller, Expert System Fuzzy
Logic controller and optimization PSO controller with PMSM to analyze all
results after using the simulation model of proposed variable speed based on
WECS. The wind turbine is coupled with PMSM. A closed loop control
system with a PI control, fuzzy, PSO in the speed loop with current
controllers. The simulation circuits for PMSM, inverter, speed and current
controllers include all realistic components of the drive system. These results
also confirmed that the transient torque and current never exceed the
maximum permissible value.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Convergence Parameter Analysis for Different Metaheuristic Methods Control Co...IJPEDS-IAES
This paper is an extension of our previous work, which discussed the
difficulty in implementing different methods of resistance emulation
techniques on the hardware due to its control constant estimation delay. In
order to get rid of the delay this paper attempts to include the meta-heuristic
methods for the control constants of the controller. To achieve the minimum
Total Harmonic Disturbance (THD) in the AC side of the converter modern
meta-heuristic methods are compared with the traditional methods. The
convergence parameters, which are primary for the earlier estimation of the
control constants, are compared with the measured parameters, tabulated and
tradeoff inference is done among the methods. This kind of implementation
does not need the mathematical model of the system under study for finding
the control constants. The parameters considered for estimation are
population size, maximum number of epochs, and global best solution of the
control constants, best THD value and execution time. MatlabTM /Simulink
based simulation is optimized with the M-file based optimization techniques
like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Cuckoo
Search Algorithm, Gravity Search Algorithm, Harmony Search Algorithm
and Bat Algorithm.
Hysteresis controllers (HC) are used to limit the torque and flux in the control band in conventional configuration of direct torque control (DTC) while in the space vector pulse width modulated (SVPWM) DTC, the HC are switched to PI or PID controllers. This paper presents a modern approach for the speed control applied on a DTC of a permanent magnet synchronous motor (PMSM) using the Cuckoo Search Optimization (CSO) algorithm in order to optimize the PI speed controller parameters of the outer loop and PID flux and torque controllers of the inner loop. The system is tested at no load and with a step change in load. The performance of the controllers is presented and the results of simulation indicate a very rapid dynamic response and the system achieves the steady state (SS.) in a very short time. Also it shows that both the SS. and dynamic performances are improved by applying of the CSO algorithm. The proposed DTC simulation model of the PMSM is presented using MATLAB / SIMULINK and capable of simulating both the steady-state and dynamic response. The CSO results are compared with another control strategy that incorporates fuzzy logic controller (FLC) with DTC.
Meta-heuristic optimization techniques are important tools to define the optimal solutions for many problems. In this paper, a new advanced artificial intelligence (AI) based direct torque control (DTC) speed drives are optimally designed and implemented in real time to achieve a high performance permanent-magnet synchronous-motor (PMSM) drive. Grey wolf (GW) algorithms are used with the standard PID-based DTC (PIDDTC) and with the DTC with fuzzy logic (FDTC) based speed controllers. DSPACE DS1202 is utilized in the real-time implementation. MATLAB SIMULINK is used to simulate the steady-state (S.S.) and dynamic responses. The overall system is tested at different operating conditions for both simulation and practical work and all results are presented. A comparison between experimental and simulation results is performed and also a comparison between different applied intelligent techniques is introduced.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Comparative Study of GA tuned and PSO tuned PI Controller Based Speed Contr...paperpublications3
Abstract: This paper presents a comparative study of Generic Algorithm (GA) and Partical Swarm Optimization (PSO) technique for determining the optimal parameters of (PI) controller for speed control of a brushless DC motor (BLDC) where the (BLDC) motor is modeled in simulink in MATLAB. The proposed technique was more efficient in improving the step response characteristics as well as reducing the steady-state error, rise time, settling time and maximum overshoot.
Metaheuristics-based Optimal Reactive Power Management in Offshore Wind Farms...Aimilia-Myrsini Theologi
The aim of the thesis is to optimally coordinate the reactive power sources in offshore wind farms in a predictive manner based to the principle of minimizing the wind farm power losses, as well the variations of the transformers tap positions. First, an accurate Neural Network-based wind speed forecasting algorithm was developed in order to counteract the uncertainty of the wind and finally, the optimal management of the available reactive sources is tackled by a metaheuristics-based method. Two different cases were investigated: a far-offshore wind farm with HVDC interconnection link and the AC connected Dutch wind farm BORSSELE.
Design and optimization of pid controller using genetic algorithmeSAT Journals
Abstract Natural evolution is mimicked by Genetic Algorithms (GAs) which is a stochastic global search method used for optimization. . In missile control systems Proportional Integral Derivative (PID) control is widely used, but due to empirically selected parameters Kp, Ki, Kd it is difficult to achieve parameter optimization. Genetic algorithm is a search algorithm that is based on natural selection and genetics principles.GA is a computational algorithm which deals with genetics of the human body. It evolves with the number of iterations. After ever iteration a better result is expected. These results are checked for the error. The fittest roots or solution are considered for the next generation based on the selection criterion. GA randomly generates the initial population of the PID control parameters according to the calculation of selection (Normalized Geometric Selection), crossover (Arithmetic Crossover) and mutation (Uniform Mutation), thus optimizing the control parameters. Mean Square Error (MSE) value is chosen as the performance assessment index. For a missile altitude control Proportional Integral Derivative (PID) controller using genetic algorithm is implemented & compared with the classical method Zeigler-Nichols (Z-N) in the paper. Z-N method is classical method which tunes the parameters of PID. The parameters of PID are difficult to tune. Tuned parameters give the optimum solution. Optimum solution generally converges to a solution having minimum error. Minimum error gives a response of the system in terms of maximum over shoot, Settling time, Rise time & Steady State Error. The designed PID with the Genetic Algorithm has much faster response than the classical method.
In this paper, the optimal control problem of a nonlinear robot manipulator in absence of holonomic constraint force based on the point of view of adaptive dynamic programming (ADP) is presented. To begin with, the manipulator was intervened by exact linearization. Then the framework of ADP and Robust Integral of the Sign of the Error (RISE) was developed. The ADP algorithm employs Neural Network technique to tune simultaneously the actor-critic network to approximate the control policy and the cost function, respectively. The convergence of weight as well as position tracking control problem was considered by theoretical analysis. Finally, the numerical example is considered to illustrate the effectiveness of proposed control design.
Priority based round robin (PBRR) CPU scheduling algorithmIJECEIAES
This paper introduce a new approach for scheduling algorithms which aim to improve real time operating system CPU performance. This new approach of CPU Scheduling algorithm is based on the combination of round-robin (RR) and Priority based (PB) scheduling algorithms. This solution maintains the advantage of simple round robin scheduling algorithm, which is reducing starvation and integrates the advantage of priority scheduling. The proposed algorithm implements the concept of time quantum and assigning as well priority index to the processes. Existing round robin CPU scheduling algorithm cannot be dedicated to real time operating system due to their large waiting time, large response time, large turnaround time and less throughput. This new algorithm improves all the drawbacks of round robin CPU scheduling algorithm. In addition, this paper presents analysis comparing proposed algorithm with existing round robin scheduling algorithm focusing on average waiting time and average turnaround time.
Fuzzy gain scheduling control apply to an RC Hovercraft IJECEIAES
The Fuzzy Gain Scheduling (FGS) methodology for tuning the ProportionalIntegral-Derivative (PID) traditional controller parameters by scheduling controlled gains in different phases, is a simple and effective application both in industries and real-time complex models while assuring the high achievements over pass decades, is proposed in this article. The Fuzzy logic rules of the triangular membership functions are exploited on-line to verify the Gain Scheduling of the Proportional-Integral-Derivative controller gains in different stages because it can minimize the tracking control error and utilize the Integral of Time Absolute Error (ITAE) minima criterion of the controller design process. For that reason, the controller design could tune the system model in the whole operation time to display the efficiency in tracking error. It is then implemented in a novel Remote Controlled (RC) Hovercraft motion models to demonstrate better control performance in comparison with the PID conventional controller.
Modeling and analysis of field-oriented control based permanent magnet synch...IJECEIAES
The permanent magnet synchronous motor (PMSM) acts as an electrical motor mainly used in many diverse applications. The controlling of the PMSM drive is necessary due to frequent usage in various systems. The conventional proportional-integral-derivative (PID) controller’s drawbacks are overcome with fuzzy logic controller (FLC) and adopted in the PMSM drive system. In this manuscript, an efficient field-oriented control (FOC) based PMSM drive system using a fuzzy logic controller (FLC) is modeled to improve the speed and torque response of the PMSM. The PMSM drive system is modeled using abc to αβ and αβ to abc transformation, 2-level space vector pulse width modulation (SVPWM), AC to DC rectifier with an inverter, followed by PMSM drive, proportional integral (PI) controller along with FLC. The FLC’s improved fuzzy rule set is adopted to provide faster speed response, less % overshoot time, and minimal steady-state error of the PMSM drive system. The simulation results of speed response, torque response, speed error, and phase currents are analyzed. The FLC-based PMSM drive is compared with the conventional PID-based PMSM drive system with better improvements in performance metrics.
Advanced Optimal PSO, Fuzzy and PI Controller with PMSM and WTGS at 5Hz Side ...IAES-IJPEDS
To use different control systems, like classical PI controller, Expert System
Fuzzy Logic Controller and optimization PSO controller. It used to control
for PMSM which worked in the integration system to Wind Energy. Wind
energy content of wind turbine, PMSM, rectifier, DC bus, inverter, filter,
load and grid. In the first step, to run the PMSM with different speeds to get
a different frequency to select the frequency on the side of a generation with
the rated speed. Second step, solve the mathematical equation to use different
values of wind speed with selected (15,20 m/s and less than with more than
15&20m/s). Third step, calculation the power generation with wind speed
(15 m/5 & 20 m/s). Fourth step, using these component system rectifier, DC
bus, inverter, filter, load & grid with WTGS & PMSM. Final step, uses
different control systems, like classical PI controller, Expert System Fuzzy
Logic controller and optimization PSO controller with PMSM to analyze all
results after using the simulation model of proposed variable speed based on
WECS. The wind turbine is coupled with PMSM. A closed loop control
system with a PI control, fuzzy, PSO in the speed loop with current
controllers. The simulation circuits for PMSM, inverter, speed and current
controllers include all realistic components of the drive system. These results
also confirmed that the transient torque and current never exceed the
maximum permissible value.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Convergence Parameter Analysis for Different Metaheuristic Methods Control Co...IJPEDS-IAES
This paper is an extension of our previous work, which discussed the
difficulty in implementing different methods of resistance emulation
techniques on the hardware due to its control constant estimation delay. In
order to get rid of the delay this paper attempts to include the meta-heuristic
methods for the control constants of the controller. To achieve the minimum
Total Harmonic Disturbance (THD) in the AC side of the converter modern
meta-heuristic methods are compared with the traditional methods. The
convergence parameters, which are primary for the earlier estimation of the
control constants, are compared with the measured parameters, tabulated and
tradeoff inference is done among the methods. This kind of implementation
does not need the mathematical model of the system under study for finding
the control constants. The parameters considered for estimation are
population size, maximum number of epochs, and global best solution of the
control constants, best THD value and execution time. MatlabTM /Simulink
based simulation is optimized with the M-file based optimization techniques
like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Cuckoo
Search Algorithm, Gravity Search Algorithm, Harmony Search Algorithm
and Bat Algorithm.
Design of spark ignition engine speed control using bat algorithm IJECEIAES
The most common problem in spark ignition engine is how to increase the speed performance. Commonly researchers used traditional mathematical approaches for designing speed controller of spark ignition engine. However, this solution may not be sufficient. Hence, it is important to design the speed controller using smart methods. This paper proposes a method for designing speed controller of a spark ignition engine using the bat algorithm (BA). The simulation is carried out using the MATLAB/SIMULINK environment. Time domain simulation is carried out to investigate the efficacy of the proposed method. From the simulation results, it is found that by designing speed controller of spark ignition engine using PI based bat algorithm, the speed performance of spark ignition engine can be enhanced both in no load condition and load condition compared to conventional PI controler.
For Induction motor is a system that works at their speed, nevertheless there are applications at which the speed operations are needed. The control of range of speed of induction motor techniques is available. The robust control is used with induction motor and the performance of the system with the controller will be improved. The mathematical model to the controller, which were coded in MATLAB. The modeling and controller will be shown by the conditions of robustness of be less than one.
In this paper, the closed loop speed controller parameters are optimized for the permanent magnet synchronous motor (PMSM) drive on the basis of the indirect field-oriented control (IFOC) technique. In this derive system under study, the speed and current controllers are implemented using the fractional order proportional, integral, and derivative (FOPID) controlling technique. FOPID is considered as efficient techniques for ripple minimization. The hybrid grey wolf optimizer (HGWO) is applied to obtain the optimal controllers in case of implementing conventional PID as well as FOPID controllers in the derive system. The optimal controller parameters tend to enhance the drive response as ripple content in speed and current, either during steady state time or transient time. The drive system is modeled and tested under various operating condition of load torque and speed. Finally, the performance for PID and FOPID are evaluated and compared within MATLAB/Simulink environment. The results attain the efficacy of the operating performance with the FOPID controller. The result shows a fast response and reduction of ripples in the torque and the current.
The speed estimation technique of induction machines has become a non-trivial task. For estimating the speed of an induction motor precisely and accurately an optimum state estimator is necessary. This paper deals with the performance analysis of induction motor drives using a recursive, optimum state estimator. This technique uses a full order state space Extended Kalman Filter (EKF) model where the rotor flux, rotor speed and stator currents are estimated. A major challenge with induction motor occurs at very low and at near zero speed. In such cases, information about the rotor parameters with respect to stator side become unobservable while using the synchronously rotating reference frame. To overcome this lost coupling effect, EKF observer linearizes the non-linear parameter in every sampling period and estimates the states and machine parameters simultaneously. The proposed algorithm is tuned to obtain least error in estimated speed. Any error found is further optimized using a non-linear fuzzy controller to obtain improved performance of the drive.
Model Validation and Control of an In-Wheel DC Motor Prototype for Hybrid El...Scientific Review SR
In this paper, a mathematical model and a controller for a DC motor are developed for the
construction of an in-wheel motor. In-wheel motors can be used in hybrid electric vehicles to provide traction
force of front or rear wheels. The model identification is achieved using a simple and low cost data acquisition
system. An Arduino Uno embedded board system is used to collect data from sensors to a computer and for
control purposes. Data processing is performed using Matlab/Simulink. Validations of the devel oped
mathematical model and controller performance are carried out by comparing simulation and experimental results.
The results obtained show that the mathematical model is accurate enough to assist in speed controller design and
implementation.
A Novel Technique for Tuning PI-controller in Switched Reluctance Motor Drive...IJECEIAES
This paper presents, an optimal basic speed controller for switched reluctance motor (SRM) based on ant colony optimization (ACO) with the presence of good accuracies and performances. The control mechanism consists of proportional-integral (PI) speed controller in the outer loop and hysteresis current controller in the inner loop for the three phases, 6/4 switched reluctance motor. Because of nonlinear characteristics of a SRM, ACO algorithm is employed to tune coefficients of PI speed controller by minimizing the time domain objective function. Simulations of ACO based control of SRM are carried out using MATLAB /SIMULINK software. The behavior of the proposed ACO has been estimated with the classical Ziegler- Nichols (ZN) method in order to prove the proposed approach is able to improve the parameters of PI chosen by ZN method. Simulations results confirm the better behavior of the optimized PI controller based on ACO compared with optimized PI controller based on classical Ziegler-Nichols method.
2.a neuro fuzzy based svpwm technique for pmsm (2)EditorJST
In the present scenario, static frequency converter based variable speed synchronous motors has
become very familiar and advantage to other drive system, especially low speed and high power applications.
Unlike the induction motor, the synchronous motor can be operated at variable power factor (leading, lagging
or unity) as desired. So, there is an increasing use of synchronous motors as adjustable speed drives. The PWM
technique is very useful to VSI drive for achieving efficient and smooth operation and free from torque
pulsations and cogging, lower volume and weight and provides a higher frequency range compared to CSI
drives. Even for voltage source inverter, the commutation circuit is not needed, if the self-extinguishing
switching devices are used. This paper proposes a concept of Neuro-fuzzy based control strategy which is used
for controlling the PMSM. The total work mainly concentrates on optimum control of PMSM with maximum
voltage utilization with less switching losses.
Induction motors are work-horse of the industry and major element in energy conversion. The replacement of the existing non-adjustable speed drives with the modern variable frequency drives would save considerable amount of electricity. A proper control scheme for variable frequency drives can enhance the efficiency and performance of the drive. This paper attempt to provide a rigorous review of various control schemes for the induction motor control and provides critical analysis and guidelines for the future research work. A detailed study of sensor based control schemes and sensor-less control schemes has been investigated. The operation, advantages, and limitations of the various control schemes are highlighted and different types of optimization techniques have been suggested to overcome the limitations of control techniques.
Three phase induction motor Induction is one of the widest spread motor due to its
robustness, simple construction, no need for complex circuits for starting. With several
available speed control techniques, this paper presents a new Proportional-Integral (PI)
controller and Artificial Neural Network (ANNs) control system based on vector control
scheme. MATLAB/SIMULINK software may be used to create a 3phase induction engine
model. To achieve the effectiveness of the controller, the system is subjected to external
disturbance. Experimental results are presented and satisfied with the controller results.
Backstepping Control for a Five-Phase Permanent Magnet Synchronous Motor DriveIJPEDS-IAES
This paper deals with the synthesis of a speed control strategy for a fivephase
permanent magnet synchronous motor (PMSM) drive based on
backstepping controller. The proposed control strategy considers the
nonlinearities of the system in the control law. The stability of the
backstepping control strategy is proved by the Lyapunov theory. Simulated
results are provided to verify the feasibility of the backstepping control
strategy.
Hybrid fuzzy-PID like optimal control to reduce energy consumptionTELKOMNIKA JOURNAL
The electric motor is one of the appliances that consume considerable energy. Therefore, the control method which can reduce energy consumption with better performance is needed. The purpose of this research is to minimize the energy consumption of the DC motor with maintaining the performance using Hybrid Fuzzy-PID. The input of the Fuzzy system is the error and power of the system. Where error is correlated with matric Q and power is correlated with matric R. Therefore, adjusting the fuzzy rule on error and power is like adjust matrices Q and R in LQR method. The proposed algorithm can reduce energy consumption. However, system response is slightly decrease shown from ISE (Integral Square Error). The energy reduction average is up to 5.58% while the average of ISE increment is up to 1.89%. The more speed variation in the system, the more energy can be saved by the proposed algorithm. While in terms of settling time, the proposed algorithm has the longest time due to higher computation time in the fuzzy system. This performance can be increased by tuning fuzzy rules. This algorithm offers a solution for a complex system which difficult to be modeled.
The aim of this research is the speed tracking of the permanent magnet synchronous motor (PMSM) using an intelligent Neural-Network based adapative backstepping control. First, the model of PMSM in the Park synchronous frame is derived. Then, the PMSM speed regulation is investigated using the classical method utilizing the field oriented control theory. Thereafter, a robust nonlinear controller employing an adaptive backstepping strategy is investigated in order to achieve a good performance tracking objective under motor parameters changing and external load torque application. In the final step, a neural network estimator is integrated with the adaptive controller to estimate the motor parameters values and the load disturbance value for enhancing the effectiveness of the adaptive backstepping controller. The robsutness of the presented control algorithm is demonstrated using simulation tests. The obtained results clearly demonstrate that the presented NN-adaptive control algorithm can provide good trackingperformances for the speed trackingin the presence of motor parameter variation and load application.
This paper presents a fast and accurate fault detection, classification and direction discrimination algorithm of transmission lines using one-dimensional convolutional neural networks (1D-CNNs) that have ingrained adaptive model to avoid the feature extraction difficulties and fault classification into one learning algorithm. A proposed algorithm is directly usable with raw data and this deletes the need of a discrete feature extraction method resulting in more effective protective system. The proposed approach based on the three-phase voltages and currents signals of one end at the relay location in the transmission line system are taken as input to the proposed 1D-CNN algorithm. A 132kV power transmission line is simulated by Matlab simulink to prepare the training and testing data for the proposed 1D- CNN algorithm. The testing accuracy of the proposed algorithm is compared with other two conventional methods which are neural network and fuzzy neural network. The results of test explain that the new proposed detection system is efficient and fast for classifying and direction discrimination of fault in transmission line with high accuracy as compared with other conventional methods under various conditions of faults.
Among the most widespread renewable energy sources is solar energy; Solar panels offer a green, clean, and environmentally friendly source of energy. In the presence of several advantages of the use of photovoltaic systems, the random operation of the photovoltaic generator presents a great challenge, in the presence of a critical load. Among the most used solutions to overcome this problem is the combination of solar panels with generators or with the public grid or both. In this paper, an energy management strategy is proposed with a safety aspect by using artificial neural networks (ANNs), in order to ensure a continuous supply of electricity to consumers with a maximum solicitation of renewable energy.
In this paper, the artificial neural network (ANN) has been utilized for rotating machinery faults detection and classification. First, experiments were performed to measure the lateral vibration signals of laboratory test rigs for rotor-disk-blade when the blades are defective. A rotor-disk-blade system with 6 regular blades and 5 blades with various defects was constructed. Second, the ANN was applied to classify the different x- and y-axis lateral vibrations due to different blade faults. The results based on training and testing with different data samples of the fault types indicate that the ANN is robust and can effectively identify and distinguish different blade faults caused by lateral vibrations in a rotor. As compared to the literature, the present paper presents a novel work of identifying and classifying various rotating blade faults commonly encountered in rotating machines using ANN. Experimental data of lateral vibrations of the rotor-disk-blade system in both x- and y-directions are used for the training and testing of the network.
This paper focuses on the artificial bee colony (ABC) algorithm, which is a nonlinear optimization problem. is proposed to find the optimal power flow (OPF). To solve this problem, we will apply the ABC algorithm to a power system incorporating wind power. The proposed approach is applied on a standard IEEE-30 system with wind farms located on different buses and with different penetration levels to show the impact of wind farms on the system in order to obtain the optimal settings of control variables of the OPF problem. Based on technical results obtained, the ABC algorithm is shown to achieve a lower cost and losses than the other methods applied, while incorporating wind power into the system, high performance would be gained.
The significance of the solar energy is to intensify the effectiveness of the Solar Panel with the use of a primordial solar tracking system. Here we propounded a solar positioning system with the use of the global positioning system (GPS) , artificial neural network (ANN) and image processing (IP) . The azimuth angle of the sun is evaluated using GPS which provide latitude, date, longitude and time. The image processing used to find sun image through which centroid of sun is calculated and finally by comparing the centroid of sun with GPS quadrate to achieve optimum tracking point. Weather conditions and situation observed through AI decision making with the help of IP algorithms. The presented advance adaptation is analyzed and established via experimental effects which might be made available on the memory of the cloud carrier for systematization. The proposed system improve power gain by 59.21% and 10.32% compare to stable system (SS) and two-axis solar following system (TASF) respectively. The reduced tracking error of IoT based Two-axis solar following system (IoT-TASF) reduces their azimuth angle error by 0.20 degree.
Kosovo has limited renewable energy resources and its power generation sector is based on fossil fuels. Such a situation emphasizes the importance of active research and efficient use of renewable energy potential. According to the analysis of meteorological data for Kosovo, it can be concluded that among the most attractive potential wind power sites are the locations known as Kitka (42° 29' 41" N and 21° 36' 45" E) and Koznica (42° 39′ 32″ N, 21° 22′30″E). The two terrains in which the analysis was carried out are mountain areas, with altitudes of 1142 m (Kitka) and 1230 m (Koznica). the same measuring height, about 84 m above the ground, is obtained for these average wind speeds: Kitka 6,667 m/s and Koznica 6,16 m/s. Since the difference in wind speed is quite large versus a difference in altitude that is not being very large, analyses are made regarding the terrain characteristics including the terrain relief features. In this paper it will be studied how much the roughness of the terrain influences the output energy. Also, that the assumption to be taken the same as to how much they will affect the annual energy produced.
Large-scale grid-tied photovoltaic (PV) station are increasing rapidly. However, this large penetration of PV system creates frequency fluctuation in the grid due to the intermittency of solar irradiance. Therefore, in this paper, a robust droop control mechanism of the battery energy storage system (BESS) is developed in order to damp the frequency fluctuation of the multi-machine grid system due to variable active power injected from the PV panel. The proposed droop control strategy incorporates frequency error signal and dead-band for effective minimization of frequency fluctuation. The BESS system is used to consume/inject an effective amount of active power based upon the frequency oscillation of the grid system. The simulation analysis is carried out using PSCAD/EMTDC software to prove the effectiveness of the proposed droop control-based BESS system. The simulation result implies that the proposed scheme can efficiently curtail the frequency oscillation.
This study investigates experimentally the performance of two-dimensional solar tracking systems with reflector using commercial silicon based photovoltaic module, with open and closed loop control systems. Different reflector materials were also investigated. The experiments were performed at the Hashemite University campus in Zarqa at a latitude of 32⁰, in February and March. Photovoltaic output power and performance were analyzed. It was found that the modified photovoltaic module with mirror reflector generated the highest value of power, while the temperature reached a maximum value of 53 ̊ C. The modified module suggested in this study produced 5% more PV power than the two-dimensional solar tracking systems without reflector and produced 12.5% more PV power than the fixed PV module with 26⁰ tilt angle.
This paper focuses on the modeling and control of a wind energy conversion chain using a permanent magnet synchronous machine. This system behaves a turbine, a generator, DC/DC and DC/AC power converters. These are connected on both sides to the DC bus, where the inverter is followed by a filter which is connected to the grid. In this paper, we have been used two types of controllers. For the stator side converter, we consider the Takagi-Sugeno approach where the parameters of controller have been computed by the theory of linear matrix inequalities. The stability synthesis has been checked using the Lyapunov theory. According to the grid side converter, the proportional integral controller is exploited to keep a constant voltage on the DC bus and control both types of powers. The simulation results demonstrate the robustness of the approach used.
The development of modeling wind speed plays a very important in helping to obtain the actual wind speed data for the benefit of the power plant planning in the future. The wind speed in this paper is obtained from a PCE-FWS 20 type measuring instrument with a duration of 30 minutes which is accumulated into monthly data for one year (2019). Despite the many wind speed modeling that has been done by researchers. Modeling wind speeds proposed in this study were obtained from the modified Rayleigh distribution. In this study, the Rayleigh scale factor (Cr) and modified Rayleigh scale factor (Cm) were calculated. The observed wind speed is compared with the predicted wind characteristics. The data fit test used correlation coefficient (R2), root means square error (RMSE), and mean absolute percentage error (MAPE). The results of the proposed modified Rayleigh model provide very good results for users.
This paper deals with an advanced design for a pump powered by solar energyto supply agricultural lands with water and also the maximum power point is used to extract the maximum value of the energy available inside the solar panels and comparing between techniques MPPT such as Incremental conductance, perturb & observe, fractional short current circuit, and fractional open voltage circuit to find the best technique among these. The solar system is designed with main parts: photovoltaic (PV) panel, direct current/direct current (DC/DC) converter, inverter, filter, and in addition, the battery is used to save energy in the event that there is an increased demand for energy and not to provide solar radiation, as well as saving energy in the case of generation more than demand. This work was done using the matrix laboratory (MATLAB) simulink program.
The objective of this paper is to provide an overview of the current state of renewable energy resources in Bangladesh, as well as to examine various forms of renewable energies in order to gain a comprehensive understanding of how to address Bangladesh's power crisis issues in a sustainable manner. Electricity is currently the most useful kind of energy in Bangladesh. It has a substantial influence on a country's socioeconomic standing and living standards. Maintaining a stable source of energy at a cost that is affordable to everyone has been a constant battle for decades. Bangladesh is blessed with a wealth of natural resources. Bangladesh has a huge opportunity to accelerate its economic development while increasing energy access, livelihoods, and health for millions of people in a sustainable way due to the renewable energy system.
When the irradiance distribution over the photovoltaic panels is uniform, the pursuit of the maximum power point is not reached, which has allowed several researchers to use traditional MPPT techniques to solve this problem Among these techniques a PSO algorithm is used to have the maximum global power point (GMPPT) under partial shading. On the other hand, this one is not reliable vis-à-vis the pursuit of the MPPT. Therefore, in this paper we have treated another technique based on a new modified PSO algorithm so that the power can reach its maximum point. The PSO algorithm is based on the heuristic method which guarantees not only the obtaining of MPPT but also the simplicity of control and less expensive of the system. The results are obtained using MATLAB show that the proposed modified PSO algorithm performs better than conventional PSO and is robust to different partial shading models.
A stable operation of wind turbines connected to the grid is an essential requirement to ensure the reliability and stability of the power system. To achieve such operational objective, installing static synchronous compensator static synchronous compensator (STATCOM) as a main compensation device guarantees the voltage stability enhancement of the wind farm connected to distribution network at different operating scenarios. STATCOM either supplies or absorbs reactive power in order to ensure the voltage profile within the standard-margins and to avoid turbine tripping, accordingly. This paper present new study that investigates the most suitable-location to install STATCOM in a distribution system connected wind farm to maintain the voltage-levels within the stability margins. For a large-scale squirrel cage induction generator squirrel-cage induction generator (SCIG-based) wind turbine system, the impact of STATCOM installation was tested in different places and voltage-levels in the distribution system. The proposed method effectiveness in enhancing the voltage profile and balancing the reactive power is validated, the results were repeated for different scenarios of expected contingencies. The voltage profile, power flow, and reactive power balance of the distribution system are observed using MATLAB/Simulink software.
The electrical and environmental parameters of polymer solar cells (PSC) provide important information on their performance. In the present article we study the influence of temperature on the voltage-current (I-V) characteristic at different temperatures from 10 °C to 90 °C, and important parameters like bandgap energy Eg, and the energy conversion efficiency η. The one-diode electrical model, normally used for semiconductor cells, has been tested and validated for the polemeral junction. The PSC used in our study are formed by the poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl C61-butyric acid methyl ester (PCBM). Our technique is based on the combination of two steps; the first use the Least Mean Squares (LMS) method while the second use the Newton-Raphson algorithm. The found results are compared to other recently published works, they show that the developed approach is very accurate. This precision is proved by the minimal values of statistical errors (RMSE) and the good agreement between both the experimental data and the I-V simulated curves. The obtained results show a clear and a monotonic dependence of the cell efficiency on the studied parameters.
The inverter is the principal part of the photovoltaic (PV) systems that assures the direct current/alternating current (DC/AC) conversion (PV array is connected directly to an inverter that converts the DC energy produced by the PV array into AC energy that is directly connected to the electric utility). In this paper, we present a simple method for detecting faults that occurred during the operation of the inverter. These types of faults or faults affect the efficiency and cost-effectiveness of the photovoltaic system, especially the inverter, which is the main component responsible for the conversion. Hence, we have shown first the faults obtained in the case of the short circuit. Second, the open circuit failure is studied. The results demonstrate the efficacy of the proposed method. Good monitoring and detection of faults in the inverter can increase the system's reliability and decrease the undesirable faults that appeared in the PV system. The system behavior is tested under variable parameters and conditions using MATLAB/Simulink.
The electrical distribution network is undergoing tremendous modifications with the introduction of distributed generation technologies which have led to an increase in fault current levels in the distribution network. Fault current limiters have been developed as a promising technology to limit fault current levels in power systems. Though, quite a number of fault current limiters have been developed; the most common are the superconducting fault current limiters, solid-state fault current limiters, and saturated core fault current limiters. These fault current limiters present potential fault current limiting solutions in power systems. Nevertheless, they encounter various challenges hindering their deployment and commercialization. This research aimed at designing a bridge-type nonsuperconducting fault current limiter with a novel topology for distribution network applications. The proposed bridge-type nonsuperconducting fault current limiter was designed and simulated using PSCAD/EMTDC. Simulation results showed the effectiveness of the proposed design in fault current limiting, voltage sag compensation during fault conditions, and its ability not to affect the load voltage and current during normal conditions as well as in suppressing the source powers during fault conditions. Simulation results also showed very minimal power loss by the fault current limiter during normal conditions.
This paper provides a new approach to reducing high-order harmonics in 400 Hz inverter using a three-level neutral-point clamped (NPC) converter. A voltage control loop using the harmonic compensation combined with NPC clamping diode control technology. The capacitor voltage imbalance also causes harmonics in the output voltage. For 400 Hz inverter, maintain a balanced voltage between the two input (direct current) (DC) capacitors is difficult because the pulse width modulation (PWM) modulation frequency ratio is low compared to the frequency of the output voltage. A method of determining the current flowing into the capacitor to control the voltage on the two balanced capacitors to ensure fast response reversal is also given in this paper. The combination of a high-harmonic resonator controller and a neutral-point voltage controller working together on the 400 Hz NPC inverter structure is given in this paper.
Direct current (DC) electronic load is a useful equipment for testing the electrical system. It can emulate various load at a high rating. The electronic load requires a power converter to operate and a linear regulator is a common option. Nonetheless, it is hard to control due to the temperature variation. This paper proposed a DC electronic load using the boost converter. The proposed electronic load operates in the continuous current mode and control using the integral controller. The electronic load using the boost converter is compared with the electronic load using the linear regulator. The results show that the boost converter able to operate as an electronic load with an error lower than 0.5% and response time lower than 13 ms.
More from International Journal of Power Electronics and Drive Systems (20)
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
2. Int J Pow Elec & Dri Syst ISSN: 2088-8694
Comperative Performance Analysis of PMSM Drive Using MPSO and ACO Techniques (Deepti Yadav)
1511
optimal solution. Another traditional method is Ziegler-Nichols (Z-N) method which is the most standard
method and widely used. But this method is tedious for systems with non-linearities such as PMSM. It
provides high overshoot in system response and not suitable to achieve fast dynamic response [6]-[8]. In
recent times artificial intelligence (AI) techniques are being adopted for efficient and optimum tuning of PID
speed controllers [9]. In this paper, speed of PMSM is controlled with the help of a PID speed controller
using AI techniques. The designing of the PID speed controller is treated as an optimization problem,
employing MPSO [10]-[17] and Ant Colony Optimization (ACO) [18]-[23] for its solution. In this work
tuning of PID controller by using MPSO and ACO technique is implemented to control speed of PMSM.
This chapter is arranged in six sections including the current introductory Section 1. The tuning of
PID speed controller using MPSO method is discussed in Section 2. Problem formulation of PID controller
that has been used in PMSM drive is discussed in Section 3. The tuning of PID speed controller using ACO
method is discussed in Section 4. PMSM simulation model and analytical results are validated in Section 5.
Finally, a summary of the paper is concluded in Section 6.
2. METHODOLOGY OF PROPOSED MODIFIED PSO
The Modified PSO technique overcome the demerits of PSO technique [24], it improve the
convergence rate and prevent the prematurely condition. When each group is divided, the group which has
maximum population at the center is preferred. It shows a particle subgroup as a central subgroup, and the
other subgroups are neighborhoods to the central subgroups, it can communicate with other subgroup near to
it and other subgroups cannot share the information with each other. By using MPSO technique the
information can transmit faster and improving efficiency of the algorithm. Accordingly, the distance of two
vectors was obtained by the space posi-tion of each particle. The Lmax denoted as the maximum distance of
any two particles. Meanwhile ||Xi (k)- Xj (k)||/Lmax was also calculated. If the ratio is smaller than a certain
value then two particles merge into one group, if the ratio is greater than a certain value then they should be
divided from the group. Each particle updates its status according to equation (1),(2) as follows [25]:
Vi(k+1)=w(k) Vi(k)+c1(k) r1(Pi-Xi(k))+ c2(k) r2(Pg-Xi(k)) (1)
Xi (k+1) = Xi (k) + Vi (k+1) (2)
Fitness function is used to evaluate every new position. In MPSO technique, the value of weight w
adjust the properly, which prevent algorithm from getting into a local optimization. In the further stage, small
one is propitious to accelerate algorithm converge. This way used is illustrated as follows:
w(k)=winitial+( winitial- wfinal)(1-k/K) (3)
c1(k)=c1initial+( c1initial – c1final)(1-k/K) (4)
c2(k)=c2initial+( c2initial – c2final)(1-k/K) (5)
k denotes current iterate time; K denotes max iterate time.
The optimized values of PID controller gains are shown in Table 1. Implemented MPSO-PID
controller is described in flowchart as shown in Figure 1.
Table 1. Values of PID gains obtained from MPSO method
Z-N Technique MPSO Technique
Kp: 0.34584 Kp: 2
Ki: 3.460165 Ki: 3
Kd: 0.008641591 Kd: 0.008
3. ISSN: 2088-8694
Int J Pow Elec & Dri Syst, Vol. 9, No. 4, December 2018 : 1510 – 1522
1512
Figure 1. Flowchart of Modified PSO PID Controller
3. PROBLEM FORMULATION
In this section, the basic concept of the PID controller is explained. The block diagram of the PID
speed controller employed in the work is illustrated in Figure 2.
Figure 2. Block diagram representation of PID speed controller
The transfer function of the PID speed controller for a continuous system is described by the
equation (6)
GPID(s) = Kp +
Ki
s
+ Kd
N
1+N.
1
s
(6)
where Kp, Ki, Kd are proportional, integral and derivative gains respectively of the PID speed controller and
N is constant filter coefficient. The gains Kp, Ki, and Kd are generated by ACO algorithm. The schematic
block diagram of PMSM drive with PID speed control system used in transient response analysis and
parameter extraction is shown in Figure 3.
4. Int J Pow Elec & Dri Syst ISSN: 2088-8694
Comperative Performance Analysis of PMSM Drive Using MPSO and ACO Techniques (Deepti Yadav)
1513
Figure 3. Block Diagram of PMSM with PID Control System
As shown in the Figure 3, the reference speed ωref is compared with the measured speed ωr and the
error signal is fed to the PID speed controller. This compares the actual and reference speed. The output of
the controller is transformed dq to abc transformation. Then, that reference current is fed to the PWM
inverter to generate the inverter’s command signals. Here the phase current Iabc and Iref are given as input.
These are compared by using the comparators. The output of the comparators is fed to the motor.
To achieve desired response through control system a cost function is implemented that describes
the performance of the system quantitatively. The transient response specifications and performance indices
taken into consideration are as follows.
3.1. Maximum Overshoot (Mp)
It is the normalized difference between the maximum speed (ωmax) attained by the PMSM and the
desired reference speed (ωref) of the motor i.e.
fm = Mp =
ωmax− ωref
ωmax
× 100 % (7)
3.2. Peak Time (tp)
It is the time taken by PMSM to reach the maximum speed (ωmax).
fp = tp (8)
3.3. Rise Time (tr)
It is the time taken by the PMSM to raise its speed from 10% to 90% of the desired reference speed.
fr = tr (9)
3.4. Settling Time (ts)
It is the time required by PMSM speed to reach and stay within a permissible tolerance band
(selected as 0.02%) of the reference speed.
fs = ts (10)
3.5. Integral Absolute Error
It is the integral of the absolute magnitude of the error which is given as:
fIAE = IAE = ∫ |e(t)|dt
∞
0
(11)
Thus summarizing, the cost function (f) is given as:
f = fm + fp + fr + fs + fIAE (12)
The objective is to minimize this function f, to achieve fast and effective speed control of PMSM.
4. ANT COLONY OPTIMIZATION ALGORITHM
ACO is defined as a meta-heuristic algorithm derived from the co-operative foraging behaviour of
5. ISSN: 2088-8694
Int J Pow Elec & Dri Syst, Vol. 9, No. 4, December 2018 : 1510 – 1522
1514
real ants [18]. The optimization problem to be solved using ACO algorithm is modeled as a graphical
problem. Virtual ants traverse the nodes of this graph in search of a minimum cost path. Each ant individually
chooses a rather poor-quality path. Better paths are found by co-operation among the entire ant population
[19],[20]. The problem of finding optimized values of Kp, Ki, Kd of the PID speed controller is represented as
a graphical problem as shown in Figure 4.
Figure 4. Graphical Representation of ACO for tuning PID Speed Controller
In this graph Kp, Ki, Kd are represented as three different vectors in which each value of the vector
acts as a node of the graph. An ant while traversing the graph must choose three nodes, one from each vector.
The choice for a node is made by the ant based on a probabilistic function [17],[18] given in equation (13):
ρij =
[hij]
α
[pij]
β
∑ [hij]
α
[pij]
β
iϵS
(13)
hij : heuristic factor dependent on problem parameters
pij : pheromone factor determining the amount of pheromone deposited at a node
α : constant determining relative importance of pheromone value at a node
β : constant determining relative importance of heuristic factor at a node
S : set of nodes not yet visited by the ant
One iteration or tour is completed when all the ants have chosen three nodes, one from each vector.
An ant while travelling marks its presence on a node by depositing pheromones. Pheromone deposition is a
way of communication between the ants. The pheromone levels at a node are updated after each tour so as to
differentiate between good and bad paths i.e. paths with low and high cost respectively. In the proposed
algorithm, two fold updating of pheromone is implemented. These are called local and global pheromone
updating rule. Local pheromone updating is carried after each ant has completed one tour according to
equation (14):
p(k)ij = p(k − 1)ij +
p.ppos
f
(14)
p(k)ij : pheromone deposited on path connecting the nodes i and j at the kth
tour
p : constant pheromone value
ppos : positive pheromone updating coefficient
C : cost function of the tour traversed by the ant
Global pheromone updating is implemented after completion of a tour by all the ants of the colony.
According to this rule the pheromone of the best and worst tours paths are updated as follows:
p(k)ij = p(k)ij
γ
+ [p(k)ij
best
+ p(k)ij
worst
] (15)
p(k)ij
𝑏𝑒𝑠𝑡
= p(k)ij
𝑏𝑒𝑠𝑡
+
p
𝑓𝑏𝑒𝑠𝑡
(16)
p(k)ij
𝑤𝑜𝑟𝑠𝑡
= p(k)ij
𝑤𝑜𝑟𝑠𝑡
−
p.pneg
𝑓𝑤𝑜𝑟𝑠𝑡
(17)
p(k)ij
best
: pheromone of nodes chosen in best tour i.e. tour resulting in lowest cost fbest
p(k)ij
worst
: pheromone of nodes chosen in worst tour i.e. tour with highest cost fworst
6. Int J Pow Elec & Dri Syst ISSN: 2088-8694
Comperative Performance Analysis of PMSM Drive Using MPSO and ACO Techniques (Deepti Yadav)
1515
γ : pheromone evaporation factor to degrade pheromone value with time, allowing ants to forget
past history of the tours travelled.
Global pheromone updating is carried out to avoid early convergence due to ants being trapped in
local minima, and allowing ants to continue searching in new directions. The ACO algorithm applied to
design an optimal PID speed controller for PMSM is as follows (Figure 5):
Step 1: Initialization
Number of ants k in the colony are initialized at the start node. Number of tours m and values of p, ppos, pneg
and λ are also set. A gain matrix with three columns one for each of the gain parameter Kp, Ki and Kd is also
constructed.
For: number of tours = 1 to m
For: number of ants = 1 to k
Step 2: Choice of nodes
Ants traverse the gain matrix and choose the values of Kp, Ki and Kd with maximum pheromone level
according to equation (13).
Step 3: Calculation of cost of tour
Cost of the tour traversed by an ant is calculated according to the cost function given in equation (12).
Step 4: Local pheromone updating
Local pheromone updating is carried out according to equation (14) until maximum ant count has been
reached. Steps 2 to 4 are repeated out until maximum ant count is reached.
Step 5: Global pheromone updating
Once maximum ant count is reached, best tour having lowest cost and worst tour having highest cost is
chosen. Pheromone of best tour nodes is increased while that of worst tour nodes is decreased according to
equations (15)-(17). Steps 2 to 5 are repeated until maximum tour count is reached.
Figure 5. Flowchart for ACO Algorithm
5. MODEL OF PMSM AND RESULTS
The reference speed of the PMSM is chosen as 1000 rpm and step function applied for load torque
with simulation time of 0.5 seconds. The values of gain parameters obtained from classical Z-N method,
MPSO and ACO method are tabulated in Table 1 and 2. The model for speed control of PMSM is as shown
in Figure 6. Matlab R2013a is used for simulation of the model.
Table 2. Values of PID gains obtained from ACO method
Z-N method ACO method
Kp: 0.34584 Kp: 9.60
Ki: 3.460165 Ki: 0.405
Kd: 0.008641591 Kd: 0.0001
7. ISSN: 2088-8694
Int J Pow Elec & Dri Syst, Vol. 9, No. 4, December 2018 : 1510 – 1522
1516
Figure 6. Model of PMSM
The motor speed is compared with reference speed by the comparator and the output is fed to the
PID controller. These controllers improve the transient response. The output of controller is fed to the dq to
abc transformation by using inverse park’s transformation. The inverter circuit is fed by the dq to abc
transformation. The output of inverter circuit is fed to PMSM. The output of PMSM is taken with the help of
bus-selector. The Rotor speed is fed back to the comparator to achieve the desired speed which is required.
The simulation is carried out under the different operating conditions such as starting, braking and load
application and removal.
Figures 7-9 illustrates the transient speed response, stator current and electromagnetic torque of the
PMSM incorporating a Z-N tuned PID speed controller under starting, speed reversal and load disturbance
conditions.
Figure 7. Starting dynamics of PMSM drive using Z-N method
8. Int J Pow Elec & Dri Syst ISSN: 2088-8694
Comperative Performance Analysis of PMSM Drive Using MPSO and ACO Techniques (Deepti Yadav)
1517
Figure 8. Speed reversal characteristics of PSMM drive using Z-N
Figure 9. Load application and Load removal characteristics of PSMM drive using Z-N
Figures 10-12 illustrates the transient speed response, stator current and electromagnetic torque of
the PMSM incorporating a MPSO tuned PID speed controller under starting, speed reversal and load
disturbance conditions.
9. ISSN: 2088-8694
Int J Pow Elec & Dri Syst, Vol. 9, No. 4, December 2018 : 1510 – 1522
1518
Figure 10. Starting dynamics of PMSM drive using MPSO method
Figure 11. Speed reversal characteristics of PSMM drive using MPSO
Figure 12. Load application and Load removal characteristics of PSMM drive using MPSO
10. Int J Pow Elec & Dri Syst ISSN: 2088-8694
Comperative Performance Analysis of PMSM Drive Using MPSO and ACO Techniques (Deepti Yadav)
1519
Figures 13-15 depict the transient speed response, stator current and electromagnetic torque of the
PMSM employing an ACO tuned PID speed controller under starting, speed reversal and load disturbance
conditions.
Figure 13. PMSM Step Response with ACO Tuning under Starting Condition
Figure 14. PMSM Step Response with ACO Tuning under Speed Reversal Condition
11. ISSN: 2088-8694
Int J Pow Elec & Dri Syst, Vol. 9, No. 4, December 2018 : 1510 – 1522
1520
Figure 15. PMSM Step Response with ACO Tuning under Load Disturbance Condition
5.1. Starting Characteristics
The motor is started at no load with 1000 rpm reference speed. The motor try to attain the reference
speed of 1000 rpm. At this instant, the torque reaches it’s no load value (zero Nm) and the stator winding
currents settle down to their normal values. The PMSM drive using AI techniques minimized the overshoot
and rise time, peak time and settling time is lower when compared to existing Z-N tuned PID speed
controller.
5.2. Speed Reversal Characteristics
The reference speed is reversed at t = 0.08s to -1000rpm. The rotor speed follows it and tries to
attain the reference value. The torque Tem also reduces, the speed settles down to its new reference value of –
1000 rpm and the torque reverts to the no load value of zero Nm. The current waveforms show a sharp
increase in the magnitude with low frequency.
5.3. Load Application and Load Removal
When the load is applied at t=0.15s. The rotor speed ωm decreases but with the increased stator
winding current and torque. When the load is removed at t=0.35s, the AI techniques responds immediately by
decreasing the stator winding current and torque. The speed of the motor changes accordingly by settling
down to its reference value.
The results presented above that MPSO and ACO algorithm are much more efficient in speed
control of PMSM as compared to the classical Z-N method. MPSO and ACO algorithm has sufficiently
suppressed the peak overshoot in speed response of PMSM during starting and speed reversal conditions
which was dominant in Z-N tuning method. The sudden drop in electromagnetic torque at the time of
application of load has also improved considerably.
The summary of extracted parameters from the sets of inset graphs from Figures 7-15, respectively
under starting of the motor, speed reversal, load application and load removal conditions are summarized in
Table 3. These parameters are analyzed during the various operating conditions of the Z-N method tuned PID
speed controller for PMSM drive.
Table 3. Dynamic Response of PMSM Drive using AI techniques and Z-N Method Tuned PID Controller
S.
No.
Type
of Speed
Controller
Motor
Characteristics
Rise
time
tr(sec)
Peak
overshoot
Mp(%)
Peak
time
tp(sec)
Settling
time
ts(sec)
Reference
time(sec)
1 Z-N
Starting 0.010 2.6 0.118 0.44 0.0
Speed Reversal 0.03 3.85 0.13 0.4 0.08
Load Application - 1.2 0.09 0.18 0.15
Load Removal - 2.1 0.06 0.38 0.35
2 MPSO
Starting 0.007 0.127 0.008 0.0088 0.0
Speed Reversal 0.087 0.48 0.088 0.44 0.08
Load Application - 0.4 0.069 0.12 0.15
Load Removal - 1.8 0.02 0.28 0.35
3 ACO
Starting 0.0052 0.00114 0.0452 0.05 0.0
Speed Reversal 0.0063 0.02062 0.0138 0.02 0.08
Load Application - -0.1119 0.0010 0.0014 0.15
Load Removal - 0.00062 0.0010 0.0014 0.35
6. CONCLUSION
The aim of the work was to design a speed controller for PMSM which has been achieved
successfully. The PID speed controller designed provides efficient load disturbance and transient response to
the motor as is evident from Table 3. The result obtained from MPSO and ACO techniques has been
compared with that derived from classical Z-N technique and have proven to be better than it. The most
important feature of this work is that online tuning of PID speed controller has been conducted using MPSO
and ACO techniques so that any dynamic conditions of the plant can be reflected immediately in the PID
gain parameters. PMSM’s have found wide application in servo robotics industry. PMSM control strategy
employing MPSO and ACO can be of immense help in precision control of robots. Moreover, this analysis
has also helped in development of new speed controller under various load conditions and techniques for
industry applications.
12. Int J Pow Elec & Dri Syst ISSN: 2088-8694
Comperative Performance Analysis of PMSM Drive Using MPSO and ACO Techniques (Deepti Yadav)
1521
REFERENCES
[1] R. Krishnan, “Permanent Magnets and Machines and Part II: Permanent Magnet Synchronous Machines and their
Control in Permanent Magnet Synchronous and Brushless DC Motor Drives,” CRC Press, Taylor & Francis
Group, Boca Raton, pp. 3-122, 225-422, 2010.
[2] B. K. Bose, “Power Electronics and Motion-Control Status and recent Trends,” IEEE Transactions on Industry
Applications, vol. 29, pp. 902-909, 1993.
[3] C. Sain, et al., “Comparative Performance Study for Closed Loop Operation of an Adjustable Speed Permanent
Magnet Synchronous Motor Drive with Different Controllers,” International Journal of Power Electronics and
Drive System (IJPEDS), vol/issue: 7(4), pp. 1085-1099, 2016.
[4] M. Tursini, et al., “Real-Time Gain Tuning of PI Controllers for High-Performance PMSM Drives,” IEEE
Transactions on Industry Applications, vol/issue: 38(4), pp. 1018-1026, 2002.
[5] A. S. Tomer and S. P. Dube, “Response Based Comparative Analysis of Two Inverter Fed Six Phase PMSM Drive
by Using PI and Fuzzy Logic Controller,” International Journal of Electrical and Computer Engineering (IJECE),
vol/issue: 6(6), pp. 2643-2657, 2016.
[6] K. J. Astrom and T. Hugglund, “PID Control and Controller Design in PID controllers Theory, Design and
Tuning,” Instrument Society of America, Research Triangle Park, second edition, pp. 59-199, 1995.
[7] J. G. Ziegler and N. B. Nichols, “Optimum settlings for automatic controllers,” Transactions of the A.S.M.E., vol.
64, pp. 759-768, 1942.
[8] F. Amin, et al., “Modelling and Simulation of Field Oriented Control based Permanent Magnet Synchronous Motor
Drive System,” Indonesian Journal of Electrical Engineering and Computer Science, vol/issue: 6(2), pp. 387-395,
2017.
[9] W. M. Utomo, et al., “Speed Tracking of Field Oriented Control Permanent Magnet Synchronous Motor Using
Neural Network,” International Journal of Power Electronics and Drive System (IJPEDS), vol/issue: 4(3): 290-
298, 2014.
[10] S. Jeong, et al., “Dvelopment and Investigation of Efficient GA/MPSO-Hybrid Algorithm Applicable to Real-
World Design Optimization,” IEEE Computational Intelligence Magazine, 2009.
[11] H. Shayeghi, et al., “Discrete MPSO algorithm based optimization of transmission lines loading in TNEP
problem,” Energy Conversion and Management, pp. 112–121, 2010.
[12] Z. Duan, et al., “Design for Multi-machine Power System damping Controller Via Particle Swarm Optimization
Approach,” SUPERGEN '09. International Conference, 2009.
[13] M. A. Shoorehdeli, et al., “Training ANFIS as an identifier with intelligent hybrid stable learning algorithm based
on particle swarm optimization and extended Kalman filter,” Fuzzy Sets and Systems, pp. 922–948, 2009.
[14] C. Karakuzu, “Fuzzy controller training using particle swarm optimization for nonlinear system control,” ISA
Transactions, pp-229-239, 2008.
[15] J. P. S. Catalão, et al., “Hybrid Wavelet-MPSO-ANFIS Approach for Short-Term Wind Power Forecasting in
Portugal,” IEEE Transactions on Sustainable Energy, pp. 50-59, 2011.
[16] D. Yadav and A. Verma, “Performance Analysis of PMSM Drive Using MPSO and MOGA Technique,” IEEE
Industrial Electronics and Applications Conference (IEACon 2016), Kota Kinabalu, Malaysia, pp-197-202, 2016.
[17] D. Yadav and A. Verma, “Comparative Performance analysis of PMSM drives using ANFIS and MPSO
techniques,” Communications in Computer and Information Science (CCIS), vol. 827, pp. 148–161, 2018.
[18] M. Dorigo and T. Stützle, “Ant Colony Optimization,” Massachusetts Institute of Technology, Bradford Book, The
MIT Press Cambridge, Massachusetts, London, England, edition 1, 2004.
[19] Y. T. Hsiao, et al., “Ant Colony Optimization for Designing of PID Controllers,” IEEE International Symposium
on Computer Aided Control Systems Design Taipei, Taiwan, pp. 321-326, 2004.
[20] Y. Chen, et al., “An Improved Ant Colony Algorithm for PID Parameters Optimization,” Second International
Conference on Intelligent Computation Technology and Automation, IEEE, pp. 157-160, 2009.
[21] I. Chiha, et al., “Tuning PID Controller Using Multiobjective Ant Colony Optimization,” Applied Computational
Intelligence and Soft Computing, Hindawi Publishing Corporation, 2012.
[22] J. He and Z. Hou, “Adaptive ant colony algorithm and its application to parameters optimization of PID
controllers,” 3rd
International Conference on Advanced Computer Control, pp. 449-451, 2011.
[23] S. Agarwal, et al., “Speed Control of PMSM Drive using Bacterial Foraging Optimization,” 4th IEEE Uttar
Pradesh Section International Conference on Electrical, Computer and Electronics (UPCON), GLA University,
Mathura, pp 84-90, 2017.
[24] A. A. A. Samat, et al., “Current PI-Gain Determination for Permanent Magnet Synchronous Motor by using
Particle Swarm Optimization,” Indonesian Journal of Electrical Engineering and Computer Science, vol/issue:
6(2), pp. 412-421, 2017.
[25] Y. Gong and Y. Qu, “Adaptive Inverse Control Based on MPSO-ANFIS for Permanent Magnet Synchronous
Motor Servo System,” IEEE Third International Conference on Intelligent Human-Machine Systems and
Cybernetics, pp. 173-176, 2011.
APPENDIX
13. ISSN: 2088-8694
Int J Pow Elec & Dri Syst, Vol. 9, No. 4, December 2018 : 1510 – 1522
1522
Table 4. PMSM Parameters
Variable Parameter Name Value Units
Rs Stator Winding Resistance 2.875 Ω
Ld Direct axis inductance 1.53 mH
Lq Quadrature axis inductance 1.53 mH
λaf
Constant flux linkage of
permanent magnets
0.175 Wb or V.s
J Moment of inertia 0.0008 Kg.m2
P No. of pole pairs 4
Table 5. MPSO Algorithm Parameters
Parameter Parameter Name Value
N No. of generation 200
Population size 20
w1 Initial inertial-weight 0.9
w2 Final inertial-weight 0.2
c1 Initial cognitive-parameter 0.5
c2 Final cognitive-parameter 2.5
r1 Initial social-parameter 0.5
r2 Final social-parameter 2.5
Table 6. ACO Algorithm Parameters
Parameter Parameter Name Value
k No. of ants 50
m No. of tour 50
p Constant pheromone value 0.06
ppos Positive pheromone coefficient 0.2
pneg Negative pheromone coefficient 0.3
γ Evaporation parameter 0.95
α Constant for pheromone factor 1
β Constant for heuristic factor 1