This document presents a method for tuning the parameters of a PID controller for a brushless DC motor using particle swarm optimization. PSO is used to find the optimal proportional, integral and derivative gains to minimize error metrics for the motor's step response. The BLDC motor is modeled in Simulink. PSO searches through potential solutions in a multi-dimensional space to determine PID parameters that produce the best step response with minimal overshoot, rise time, settling time and steady state error. The results show the PSO-tuned PID controller achieves better dynamic performance than other methods.
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.
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.
Comparison of cascade P-PI controller tuning methods for PMDC motor based on ...IJECEIAES
In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.
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.
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.
Comparison of cascade P-PI controller tuning methods for PMDC motor based on ...IJECEIAES
In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.
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.
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.
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.
Comparison of different controllers for the improvement of Dynamic response o...IJERA Editor
As the technology is fast changing, there is more and more use of machine intelligence in modern motor controllers. These controllers are employed in advanced electric motor drives in particular, the present day Induction motor drives. These systems emulate the human logic. This is particularly useful when the application has poorly defined mathematical model. In this present paper the analysis of fuzzy logic as the artificial intelligence is used. The comparative study of Fuzzy PI, Fuzzy MRAC is made. There is always a compromise of the cost and complexity. So this paper presents a new approach and its dynamic response in comparison to the Fuzzy PI and Fuzzy MRAC. The proposed controller is Fuzzy PI with scaling factors. This approach is validated with the Speed, torque responses of Indirect vector controlled Induction motor (IVCIM) drive.
Investigation of Artificial Neural Network Based Direct Torque Control for PM...cscpconf
This paper investigates solution for the chronically and the biggest problem of direct torque control scheme: high torque ripple. Otherwise, another main problem faced in direct torque control method is difficulties due to complex algorithm to get high performance control for industrial motors. The purpose of this paper is to simplify the control structure by using artificial neural networks learning abilities and to investigate the affects of this structure on torque performance of motor. For this purpose, two different artificial neural networks have been suggested replacing the optimal switching vector selection and flux sector determination process of conventional direct torque control method. Matlab/Simulink based numerical simulations have been carried out to compare motor performances with conventional control structure and proposed artificial neural network based structure. It has been observed that the dynamic response of motor is faster and torque ripple and the controller complexity of the conventional control system has been reduced with the proposed technique.
Enhanced Direct Torque Control for Doubly Fed InductionMachine by Active Lear...CSCJournals
The term Direct Torque Control (DTC) originally is referred to a strategy which provides good transient and steady-state performance but it has also some negative aspects, such as non accuracy of flux, torque estimator, torque and flux ripple caused by non-optimality of switching and imprecision in motor model which are known as an inherent characteristic of DTC. This paper explores reducing of flux and torque ripple with using trial and error actively as a method called Active Learning Method (ALM) in DTC for Doubly Fed Induction Machine (DFIM) which are the motors or generators having twist on both stator and rotor subsequence power is transferred between shaft and system. DFIM is linked to the grid within the stator and the rotor is fed by an Indirect Matrix Converter (IMC). The function of IMC is similar to the direct one, although it has the line and load bridges separated. We analysis the usage of four-step commutation in rectifier stage of IMC to achieve the object of the losses’ reduction which are caused by snubber circuit. ALM adopts itself with torque and flux estimators and estimates the outputs with regards to the errors in torque and flux estimation by repetition therefore achieves the object of omitting inaccuracies in control system hence confirming the effectiveness. Another concept in ALM called Ink Drop Spread (IDS) handles different modeling target to predict on the data consequensing a behavior curve in DTC. According to the simulation results, it is proved that a significant torque and stator flux ripple reduction are obtained.
Type 1 versus type 2 fuzzy logic speed controllers for brushless DC motors IJECEIAES
This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2FLC exhibited better performance than T1FLC.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Speed and Torque Control of Mechanically Coupled Permanent Magnet Direct Curr...IDES Editor
A new controller is designed for speed and torque
control of a Permanent Magnet DC motor based on
measurements of speed and current. This research work
focuses on investigating the effects of control of the speed and
torque of two brushless dc motors that are mechanically
coupled. Two controller design methods: the Root Locus
method and Bode Plot method as well as two controllers:
Proportional-Integral-Derivative (PID) and Proportional-
Integral (PI) are used to obtain the control objectives of speed
control and torque control. The simulation is performed using
MATLAB/SIMULINK software. The effects of varying the
controller gains on the system performance is studied and
quantified. The simulation results show that the speed control
objectives of the motor are satisfied even in the case of torque
disturbance from the other motor.
Estimating the parameters of a geared DC motor is crucial in terms of its non-linear features. In this paper, parameters of a geared DC motor are estimated genetically. Mathematical model of the DC motor is determined by Kirchhoff’s law and dynamic model of its shafts and gearbox. Parameters of the geared DC motor are initially estimated by MATLAB/SIMULINK. The estimated parameters are defined as initial values for Genetic Algorithm (GA) to minimize the error of the simulated and actual angular trajectory captured by an encoder. The optimal estimated model of the geared DC motor is validated by different voltages as the input of the actual DC motor and its mathematical model. The results and numerical analysis illustrate it can be ascertained that GA is appropriate to estimate the parameters of platforms with non linear characteristics.
STATOR FLUX OPTIMIZATION ON DIRECT TORQUE CONTROL WITH FUZZY LOGIC cscpconf
The Direct Torque Control (DTC) is well known as an effective control technique for high
performance drives in a wide variety of industrial applications and conventional DTC technique
uses two constant reference value: torque and stator flux. In this paper, fuzzy logic based stator
flux optimization technique for DTC drives that has been proposed. The proposed fuzzy logic
based stator flux optimizer self-regulates the stator flux reference using induction motor load situation without need of any motor parameters. Simulation studies have been carried out with Matlab/Simulink to compare the proposed system behaviors at vary load conditions. Simulation results show that the performance of the proposed DTC technique has been improved and especially at low-load conditions torque ripple are greatly reduced with respect to the conventional DTC
TORQUE CONTROL OF AC MOTOR WITH FOPID CONTROLLER BASED ON FUZZY NEURAL ALGORITHMijics
Nowadays in the complicated systems, design of proper and implementable controller has a most importance. With respect to ability of fractional order systems in complicated systems identification as a first order fractional system with time delay, usage of fractional order PID has a proper result. From one side flexibility of fractional calculus than integer order has been topics of interest to the researchers. From another side, PMSM motors which are one the AC motor types, has been allocated largely accounted position in industry and used in variety applications. Therefore in this paper torque direct control of PMSM motors with FOPID based on model is proposed. Also fuzzy neural controllers are widely considered. Reason of this is success of fuzzy neural controller in control and identification of uncertain and complicated systems. The proposed method in this paper is combination of FOPID controller with fuzzy neural supervision system which with coefficients setting of this controller, control operation of PMSM will improve. Results of proposed method show the ability of proposed technique in reference signal tracking, elimination of disturbances effects and functional robustness in presence of noise and uncertainty. The results show the error averagely in three condition, nominal form, step disturbance and noise and uncertainly will decrease 11.66% in proposed method (FNFOPID) with Integral Square Error criterion and 7.69% with Integral Absolute Error criterion in comparison to FOPID.
Speed control of Separately Excited DC Motor using various Conventional Contr...IJERA Editor
This paper presents comparative study of various conventional controllers such as Proportional (P), Proportional
Derivative (PD), Proportional integral (PI) and Proportional Integral Derivative (PID) controller for a speed
control of a Separately Excited Direct Current (SEDC) motor by using MATLAB / SIMULINK. All controllers
have their specific function for a particular task. The speed control normally done by feedback loop or closed
loop. The aim of development of this paper is towards providing efficient and simple method for controlling the
speed. The auto - tuning method are used to for this paper to control the speed. Among all this controllers PI
controller are frequently utilized in industries as compared to PID because Derivative action are sensitive to
noise, though PID controller will improve the steady state error. Additionally it produces less overshoot,
decreasing rise time and settling time. The MATLAB simulation are analysed and compared by using the auto
tuning method.
Keywords - Proportional (P), Proportional – Derivative (PD), Proportional - Integral (PI), Proportional –
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
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.
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.
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.
Comparison of different controllers for the improvement of Dynamic response o...IJERA Editor
As the technology is fast changing, there is more and more use of machine intelligence in modern motor controllers. These controllers are employed in advanced electric motor drives in particular, the present day Induction motor drives. These systems emulate the human logic. This is particularly useful when the application has poorly defined mathematical model. In this present paper the analysis of fuzzy logic as the artificial intelligence is used. The comparative study of Fuzzy PI, Fuzzy MRAC is made. There is always a compromise of the cost and complexity. So this paper presents a new approach and its dynamic response in comparison to the Fuzzy PI and Fuzzy MRAC. The proposed controller is Fuzzy PI with scaling factors. This approach is validated with the Speed, torque responses of Indirect vector controlled Induction motor (IVCIM) drive.
Investigation of Artificial Neural Network Based Direct Torque Control for PM...cscpconf
This paper investigates solution for the chronically and the biggest problem of direct torque control scheme: high torque ripple. Otherwise, another main problem faced in direct torque control method is difficulties due to complex algorithm to get high performance control for industrial motors. The purpose of this paper is to simplify the control structure by using artificial neural networks learning abilities and to investigate the affects of this structure on torque performance of motor. For this purpose, two different artificial neural networks have been suggested replacing the optimal switching vector selection and flux sector determination process of conventional direct torque control method. Matlab/Simulink based numerical simulations have been carried out to compare motor performances with conventional control structure and proposed artificial neural network based structure. It has been observed that the dynamic response of motor is faster and torque ripple and the controller complexity of the conventional control system has been reduced with the proposed technique.
Enhanced Direct Torque Control for Doubly Fed InductionMachine by Active Lear...CSCJournals
The term Direct Torque Control (DTC) originally is referred to a strategy which provides good transient and steady-state performance but it has also some negative aspects, such as non accuracy of flux, torque estimator, torque and flux ripple caused by non-optimality of switching and imprecision in motor model which are known as an inherent characteristic of DTC. This paper explores reducing of flux and torque ripple with using trial and error actively as a method called Active Learning Method (ALM) in DTC for Doubly Fed Induction Machine (DFIM) which are the motors or generators having twist on both stator and rotor subsequence power is transferred between shaft and system. DFIM is linked to the grid within the stator and the rotor is fed by an Indirect Matrix Converter (IMC). The function of IMC is similar to the direct one, although it has the line and load bridges separated. We analysis the usage of four-step commutation in rectifier stage of IMC to achieve the object of the losses’ reduction which are caused by snubber circuit. ALM adopts itself with torque and flux estimators and estimates the outputs with regards to the errors in torque and flux estimation by repetition therefore achieves the object of omitting inaccuracies in control system hence confirming the effectiveness. Another concept in ALM called Ink Drop Spread (IDS) handles different modeling target to predict on the data consequensing a behavior curve in DTC. According to the simulation results, it is proved that a significant torque and stator flux ripple reduction are obtained.
Type 1 versus type 2 fuzzy logic speed controllers for brushless DC motors IJECEIAES
This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2FLC exhibited better performance than T1FLC.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Speed and Torque Control of Mechanically Coupled Permanent Magnet Direct Curr...IDES Editor
A new controller is designed for speed and torque
control of a Permanent Magnet DC motor based on
measurements of speed and current. This research work
focuses on investigating the effects of control of the speed and
torque of two brushless dc motors that are mechanically
coupled. Two controller design methods: the Root Locus
method and Bode Plot method as well as two controllers:
Proportional-Integral-Derivative (PID) and Proportional-
Integral (PI) are used to obtain the control objectives of speed
control and torque control. The simulation is performed using
MATLAB/SIMULINK software. The effects of varying the
controller gains on the system performance is studied and
quantified. The simulation results show that the speed control
objectives of the motor are satisfied even in the case of torque
disturbance from the other motor.
Estimating the parameters of a geared DC motor is crucial in terms of its non-linear features. In this paper, parameters of a geared DC motor are estimated genetically. Mathematical model of the DC motor is determined by Kirchhoff’s law and dynamic model of its shafts and gearbox. Parameters of the geared DC motor are initially estimated by MATLAB/SIMULINK. The estimated parameters are defined as initial values for Genetic Algorithm (GA) to minimize the error of the simulated and actual angular trajectory captured by an encoder. The optimal estimated model of the geared DC motor is validated by different voltages as the input of the actual DC motor and its mathematical model. The results and numerical analysis illustrate it can be ascertained that GA is appropriate to estimate the parameters of platforms with non linear characteristics.
STATOR FLUX OPTIMIZATION ON DIRECT TORQUE CONTROL WITH FUZZY LOGIC cscpconf
The Direct Torque Control (DTC) is well known as an effective control technique for high
performance drives in a wide variety of industrial applications and conventional DTC technique
uses two constant reference value: torque and stator flux. In this paper, fuzzy logic based stator
flux optimization technique for DTC drives that has been proposed. The proposed fuzzy logic
based stator flux optimizer self-regulates the stator flux reference using induction motor load situation without need of any motor parameters. Simulation studies have been carried out with Matlab/Simulink to compare the proposed system behaviors at vary load conditions. Simulation results show that the performance of the proposed DTC technique has been improved and especially at low-load conditions torque ripple are greatly reduced with respect to the conventional DTC
TORQUE CONTROL OF AC MOTOR WITH FOPID CONTROLLER BASED ON FUZZY NEURAL ALGORITHMijics
Nowadays in the complicated systems, design of proper and implementable controller has a most importance. With respect to ability of fractional order systems in complicated systems identification as a first order fractional system with time delay, usage of fractional order PID has a proper result. From one side flexibility of fractional calculus than integer order has been topics of interest to the researchers. From another side, PMSM motors which are one the AC motor types, has been allocated largely accounted position in industry and used in variety applications. Therefore in this paper torque direct control of PMSM motors with FOPID based on model is proposed. Also fuzzy neural controllers are widely considered. Reason of this is success of fuzzy neural controller in control and identification of uncertain and complicated systems. The proposed method in this paper is combination of FOPID controller with fuzzy neural supervision system which with coefficients setting of this controller, control operation of PMSM will improve. Results of proposed method show the ability of proposed technique in reference signal tracking, elimination of disturbances effects and functional robustness in presence of noise and uncertainty. The results show the error averagely in three condition, nominal form, step disturbance and noise and uncertainly will decrease 11.66% in proposed method (FNFOPID) with Integral Square Error criterion and 7.69% with Integral Absolute Error criterion in comparison to FOPID.
Speed control of Separately Excited DC Motor using various Conventional Contr...IJERA Editor
This paper presents comparative study of various conventional controllers such as Proportional (P), Proportional
Derivative (PD), Proportional integral (PI) and Proportional Integral Derivative (PID) controller for a speed
control of a Separately Excited Direct Current (SEDC) motor by using MATLAB / SIMULINK. All controllers
have their specific function for a particular task. The speed control normally done by feedback loop or closed
loop. The aim of development of this paper is towards providing efficient and simple method for controlling the
speed. The auto - tuning method are used to for this paper to control the speed. Among all this controllers PI
controller are frequently utilized in industries as compared to PID because Derivative action are sensitive to
noise, though PID controller will improve the steady state error. Additionally it produces less overshoot,
decreasing rise time and settling time. The MATLAB simulation are analysed and compared by using the auto
tuning method.
Keywords - Proportional (P), Proportional – Derivative (PD), Proportional - Integral (PI), Proportional –
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
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.
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.
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.
Quali sono le cause della pancia gonfia? E l’eccessiva aria nella pancia (detta anche meteorismo) da che cosa è causata? Intolleranze alimentari, colite, eccesso di cibo, cibo non adatto e mangiato in fretta, stress, ansia, alcune condizioni in particolari stati della vita (menopausa, gravidanza) quanto influiscono? E, infine, perché è cosi difficile risolvere il problema della pancia gonfia? In questo articolo trovi le risposte a tutte queste domande e molto altro ancora.
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.
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.
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.
This paper presents an enhanced nonlinear PID (NPID) controller to follow a preselected speed profile of brushless DC motor drive system. This objective should be achieved regardless the parameter variations, and external disturbances. The performance of enhanced NPID controller will be investigated by comparing it with linear PID control and fractional order PID (FOPID) control. These controllers are tested for both speed regulation and speed tracking. The optimal parameters values of each control technique were obtained using Genetic Algorithm (GA) based on a certain cost function. Results shows that the proposed NPID controller has better performance among other techniques (PID and FOPID controller).
Fuzzy logic Technique Based Speed Control of a Permanent Magnet Brushless DC...IJMER
This paper presents an analysis by which the dynamic performances of a permanent magnet
brushless dc (PMBLDC) motor drive with different speed controllers can be successfully predicted. The
control structure of the proposed drive system is described. The dynamics of the drive system with a
classical proportional-integral-derivative (PID) and Fuzzy-Logic (FL) speed controllers are presented.
The simulation results for different parameters and operation modes of the drive system are investigated
and compared. The results with FL speed controller show improvement in transient response of the
PMBLDC drive over conventional PID controller. Moreover, useful conclusions stemmed from such a
study which is thought of good use and valuable for users of these controllers
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.
Speed Control of Brushless Dc Motor Using Fuzzy Logic Controlleriosrjce
This paper presents a control scheme of a fuzzy logic for the brushless direct current (BLDC)
permanent magnet motor drives. The mathematical model of BLDC motor and fuzzy logic algorithm is derived.
The controller is designed to tracks variations of speed references and stabilizes the output speed during load
variations. The BLDC has some advantages compare to the others type of motors, however the nonlinearity of
the BLDC motor drive characteristics, because it is difficult to handle by using conventional proportionalintegral
(PI) controller. The BLDC motor is fed from the inverter where the rotor position and current
controller is the input. In order to overcome this main problem, the fuzzy logic control is learned continuously
and gradually becomes the main effective control. The effectiveness of the proposed method is verified by
develop simulation model in MATLAB-Simulink program. The simulation results show that the proposed fuzzy
logic controller (FLC) produce significant improvement control performance compare to the PI controller for
both condition controlling speed reference variations and load disturbance variations. Fuzzy logic is introduced
in order to suppressing the chattering and enhancing the robustness of the controlled system. Fuzzy boundary
layer is developed to provide smother transition to the equivalent control. Smaller overshoot in the speed
response and much better disturbance rejecting capabilities.
6. performance analysis of pd, pid controllers for speed control of dc motork srikanth
Aim of this paper different Proportional-Integral- Derivative (PID) controller fine-tuning techniques are investigated for speed control of DC motor. At the start PID controller parameters for different tuning techniques are involved and then applied to the DC motor model for motion (speed) control. Simulation results are display, using these controllers, objective of this paper, the performance of a choose dc motor controlled by a proportional-integral-derivative (PID) controller is below the similar transient conditions and performances are compared.
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Brushless DC Motor Drive during Speed Regulation with Artificial Neural Netwo...IJERA Editor
Brushless DC motor, at this moment is extensively used being many industrial functions due to the different
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IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
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To Graph or Not to Graph Knowledge Graph Architectures and LLMs
V04507125128
1. Pooja Sharma et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 5( Version 7), May 2014, pp.125-128
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Tuning of PID Controller for A Linear Brushless DC Motor using
Swarm Intelligence Technique
Pooja Sharma, Rajeev Gupta
UCE, RTU Kota Kota, India
UCE, RTU Kota Kota, India
Abstract
An Optimal Design of PID Controller is proposed in this paper. The Methodology of PSO Algorithm is utilized
to search the optimal parameters of Proportional Integral Derivative (PID) Controller for BLDC Motor. PSO is
an Evolutionary Optimization Technique. A Linear Brushless DC Motors are known for higher efficiency and
lower maintenance. The Brushless DC Motor is modeled in Simulink & tuning of PID controller using PSO is
implemented in MATLAB. This Method was more efficient for Step Response Characteristics.
Keywords—Brushless DC Motor, Particle Swarm Optimization ,PID Controller, Optimal Control.
I. INTRODUCTION
There are two types of DC Motors which are
used on a large scale in industries or many
applications .They are Conventional DC or Brushless
DC motor .The first one is the conventional DC
motor where the flux is produced by current through
field coil of stationary pole structure [1] .The Second
one is BLDC Motor where permanent Magnet
Provides the necessary air gap flux instead of wire
wound field poles.
BLDC Motor has the advantage of No
Mechanical Commutator, Lower Maintenance also
has simple structure, higher efficiency, and high force
& has a high Starting Torque versus falling speed
Characteristics which helps high starting torque &
helps to prevent sudden load rise [2]. The BLDC
Motors are especially used in the industries,
production, aeronautics, medicine; consumer &
industrial automations .The BLDC Motors are well
driven by dc voltage. They have no commutation that
is done by electronics application (Hall effect
Sensors).Recently Many Control methodologies such
as optimal control[4] ,nonlinear control[3], variable
structure control[5] & adaptive control[6] have
widely used for Linear Brushless DC motor .However
These approaches are either complex in theoretical
Bases or difficult to implement[7].
The PID (proportional integral & derivative)
Controller is widely used in various field as control
engineering, if there are stability is desired, then PID
Controller could be very useful. PID controller is the
controller parameters tuning process. In a PID
controller, each mode (proportional, integral and
derivative mode) has a gain to be tuned, giving as a
result three variables involved in the tuning process.
PSO algorithm is used to select optimal control gains.
The Design of BLDC Motor involves a
complex process such as modeling, control scheme
selection, simulation & parameters tuning etc .various
control solutions methods are proposed for speed
control design of BLDC Motor. However, PSO PID
Controller Algorithm is an easy implementation,
flexible & highly reliable. It is firstly introduced by
Kennedy & Eberhart [14] is one of the method Of
learning algorithms .it is Motivated by the behavior
of organism , such as fish schooling & bird flocking
.it is a well Balanced mechanism to enhance the
Global & local exploration abilities.
In This Paper, an optimal PID Controller for
a general second Order system is developed using
PSO approach. The new PID tuning Algorithm is
applied to the speed control of BLDC Motors.
II. BRUSHLESS DC MOTORS
BLDC motors are a derivative of the most commonly
used DC motor, the brushed DC motor, and they
share the same torque and speed performance curve
characteristics. The major difference between the two
is the use of brushes. BLDC motors do not have
brushes (hence the name "brushless DC") and must
be electronically commutated [17]. Commutation is
the act of changing the motor phase currents at the
appropriate times to produce rotational torque .DC
motors use mechanical commutators and brushes to
achieve the commutation .BLDC Motors use Hall
Effect sensors in place of commutators.
The stators of BLDC motors are the coils,
and the rotors are the permanent magnets. The stators
develop the magnetic fields to make the rotor rotating
.The BLDC Motor operates in many modes (phases),
but the most common is the 3-phase.The 3-phase has
better efficiency and gives quite low torque. The 3-
phase has a very good precision in control .The
characteristics equations of BLDC motors can be
represented as:
RESEARCH ARTICLE OPEN ACCESS
2. Pooja Sharma et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 5( Version 7), May 2014, pp.125-128
www.ijera.com 126 | P a g e
𝑣𝑎𝑝𝑝 (t) = L
𝑑𝑖(𝑡)
𝑑𝑡
+R. i (t) + 𝑣𝑎𝑝𝑝 (t) (1)
𝑣 𝑒𝑚𝑓 = 𝐾𝑏 .ω (t) (2)
T (t) =𝐾𝑖. i (t) (3)
T(t) = J
𝑑𝜔 (𝑡)
𝑑𝑡
+ D.𝜔(𝑡) (4)
Where 𝑣𝑎𝑝𝑝 (t) is the applied voltage, ω (t) is the rotor
speed,
L is the inductance of the stator, i(t) is the current of
the circuit, R is resistance of the stator, 𝑣 𝑒𝑚𝑓 (t) is the
back electromotive force , T is the torque of motor, D
is viscous coefficient , J is the moment of inertia ,
𝐾𝑡 is the motor torque constant , and 𝐾𝑏 is the back
electromotive force constant.
Fig.1 shows the block diagram of BLDC Motor, from
the characteristics equations of the BLDC motor, the
transfer function of speed model is obtained:
𝜔(𝑠)
𝑣 𝑎𝑝𝑝 (𝑠)
=
𝐾𝑡
𝐿.𝐽 .𝑆2+ 𝐿𝐷+𝑅𝐽 𝑆+𝐾 𝑡 𝐾 𝑏
(5)
Fig.1 The block diagram of BLDC motor
The parameters of the motors used for simulation are
as follows:
Table I
PARAMETERS OF THE MOTOR
PARAMETERS Values and units
R 21.2 Ω
𝐾𝑏 0.1433 Vs 𝑟𝑎𝑑−1
D 1*10−4
Kg-m s/ rad
L 0.052 H
𝐾𝑏 0.1433 Kg-m/A
J 1*10−5
Kgm 𝑠2
/rad
III. OVERVIEW OF PARTICLE SWARM
OPTIMIZATION
PSO is an easy & smart artificial techniques
and a evolutionary computation technique which is
developed by Kennedy & Eberhart [13] .it is used to
explore the search space of a given problem to find
the settings or parameters required to optimize a
particular objective. It is based on following two
concepts: (i) The idea of swarm intelligence based on
the observation of swarming habits by certain kinds
of animals (such as birds and fish), (ii) The field of
evolutionary computation .The assumption is basic of
PSO [16].
For n-variables optimization problem a flock
of particles are put into the n-dimensional search
space with randomly chosen velocities and positions
knowing their best values, so far (𝑃𝑏𝑒𝑠𝑡 ) and the
position in the n-dimensional space. The velocity of
each particle, adjusted accordingly to its own
experience and the other particles flying experience.
For example, the 𝑖𝑡 particle is represented as:
𝑋𝑖 =(𝑥𝑖1,𝑥𝑖2,𝑥𝑖3……………..𝑥𝑖𝑑 )in the d-dimensional
space,
the best previous positions of the 𝑖𝑡 particle is
represented as:
𝑃𝑏𝑒𝑠𝑡 =
(𝑃𝑏𝑒𝑠𝑡 𝑖,1,𝑃𝑏𝑒𝑠𝑡 𝑖,2,𝑃𝑏𝑒𝑠𝑡 𝑖,3………………𝑃𝑏𝑒𝑠𝑡 𝑖,𝑑 )
The index of the best particle among the group is
𝑔 𝑏𝑒𝑠𝑡 . Velocity of the 𝑖𝑡 particle is represented as:
𝑉𝑖 = (𝑉𝑖,1,𝑉𝑖,2 𝑉𝑖,3………….𝑉𝑖,𝑑)
The updated velocity and the distance from 𝑃𝑏𝑒𝑠𝑡 𝑖,𝑑 to
𝑔 𝑏𝑒𝑠𝑡 𝑖,𝑑 is given as[13] :
𝑣𝑖,𝑚
(𝑡+1)
=w.𝑣𝑖,𝑚
(𝑡)
+𝑐1*rand()*(𝑃𝑏𝑒𝑠𝑡𝑖,𝑚 -𝑥 𝑚
(𝑡)
)+𝑐2*
rand()*𝑔𝑏𝑒𝑠𝑡 𝑚 - 𝑥𝑖,𝑚
(𝑡)
)
(6)
𝑥𝑖,𝑚
(𝑡+1)
=𝑥 𝑚
(𝑡)
+𝑣 𝑚
(𝑡+1)
(7)
i= 1, 2........, n
m= 1, 2,......d
n Number of particles in the group
d Dimension
t Pointer of iterations (generations)
𝑣𝑖,𝑚
(𝑡)
Velocity of particle I at iteration t
w Inertia weight factor
𝑐1,𝑐2 Acceleration constant
rand () Random number between 0 and 1
𝑥𝑖,𝑑
(𝑡)
Current position of particle i at
iterations
𝑃𝑏𝑒𝑠𝑡𝑖 Best previous position of the ith
particle
𝑔 𝑏𝑒𝑠𝑡 Best particle among all the particles in the
population
IV. IMPLEMENTATION OF PSO-PID
FOR BLDC MOTOR
In This paper a time domain criterion is used
for evaluating the PID Controller .A set of good
control parameters P,I and D
3. Pooja Sharma et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 5( Version 7), May 2014, pp.125-128
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Can yield a good step response that will result in
performance criteria minimization in the time domain
.These performance criteria in the time domain
include the overshoot, rise time,
Settling time, and steady state error [13]. Therefore,
the performance criterion is defined as follows:
W (K) = (1- 𝑒−𝛽
).(𝑀𝑝 + 𝐸𝑠𝑠) + 𝑒−𝛽
.(𝑡 𝑠 - 𝑡 𝑟)
where K is [P,I,D]and β is weightening factor. The
performance criterion W (K) can satisfy the designer
requirement using the weightening factor β value. β
can set to be larger than 0.5 to reduce the overshoot
and steady state error, also can set smaller 0.5 to
reduce the rise time and settling time. The optimum
selection of β depends on the designer‟s requirement
and the characteristics of the plant under control. In
BLDC motor speed control system the lower β would
lead to more optimum responses. In this paper, due to
trial, β is set to be 0.5 to optimum the step response
of speed control system.
The fitness function is reciprocal of the
performance criterion, in the other words,
f =
1
𝑊(𝐾)
In this paper a PSO-PID controller is used to
find the optimal values of BLDC speed control
system.
Fig.2 shows the block diagram of optimal
PID control for the BLDC motor.
Fig.2 optimal PID control
In the proposed PSO method each particle
contains three members P, I and D. It means that the
search space has three dimension and particles must
„fly‟ in a three dimensional space.
The flow chart of PSO-PID controller is
shown in Fig. 3.
Fig.3 Flowchart of PSO-PID control system
V. RESULTS
To control the speed of LBDC motor at
500rpm, according to the trials, the following PSO
parameters are used to verify the performance of the
PSO-PID controller parameters:
population size : 25
𝑤 𝑚𝑎𝑥 = 0.9 , 𝑤 𝑚𝑖𝑛 = 0.4
𝑐1 =𝑐2= 0.5
Iteration = 100;
Fig.4 Step response of BLDC motor with PSO tune
PID controller
4. Pooja Sharma et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 5( Version 7), May 2014, pp.125-128
www.ijera.com 128 | P a g e
TABLE II
PERFORMANCE OF THE PSO-PID
CONTROLLER
Parameters Proposed Method Mehdi
Nasri et.
Al. [21]
[KP KI KD] [ 90.3281,85.2238
,16.7163]
[190.0176,5
0,0.039567]
Rise Time(ms) 4.7733e-004 0.3038
Max
Overshoot (%)
0 0
Steady State
error
0.5000 0.77186
Settling time 8.5014e-007 0.60116
VI. CONCLUSIONS
In this paper a novel method to determine
PID controller parameters using the PSO method is
proposed. Obtained through simulation of BLDC
motor, the results show that the proposed controller
can perform an efficient search for the optimal PID
controller. This method can improve the dynamic
Performance of the system in a better way.
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