Enviar pesquisa
Carregar
Optimum tuning of pid controller for a permanent magnet brushless dc motor
•
0 gostou
•
342 visualizações
IAEME Publication
Seguir
Denunciar
Compartilhar
Denunciar
Compartilhar
1 de 12
Baixar agora
Baixar para ler offline
Recomendados
Robust model reference adaptive control for a second order system 2
Robust model reference adaptive control for a second order system 2
IAEME Publication
FUZZY LOGIC CONTROLLER TUNNING VIA ADAPTIVE GENETIC ALGORITHM APPLIED TO AIRC...
FUZZY LOGIC CONTROLLER TUNNING VIA ADAPTIVE GENETIC ALGORITHM APPLIED TO AIRC...
Ahmed Momtaz Hosny, PhD
Optimal PID Controller Design for Speed Control of a Separately Excited DC Mo...
Optimal PID Controller Design for Speed Control of a Separately Excited DC Mo...
ijscmcj
Computation of Simple Robust PI/PID Controller Design for Time-Delay Systems ...
Computation of Simple Robust PI/PID Controller Design for Time-Delay Systems ...
IRJET Journal
Performance analysis of a second order system using mrac
Performance analysis of a second order system using mrac
iaemedu
Multi parametric model predictive control based on laguerre model for permane...
Multi parametric model predictive control based on laguerre model for permane...
IJECEIAES
Tuning of PID, SVFB and LQ Controllers Using Genetic Algorithms
Tuning of PID, SVFB and LQ Controllers Using Genetic Algorithms
International Journal of Engineering Inventions www.ijeijournal.com
A comparative study of controllers for stabilizing a rotary inverted pendulum
A comparative study of controllers for stabilizing a rotary inverted pendulum
ijccmsjournal
Recomendados
Robust model reference adaptive control for a second order system 2
Robust model reference adaptive control for a second order system 2
IAEME Publication
FUZZY LOGIC CONTROLLER TUNNING VIA ADAPTIVE GENETIC ALGORITHM APPLIED TO AIRC...
FUZZY LOGIC CONTROLLER TUNNING VIA ADAPTIVE GENETIC ALGORITHM APPLIED TO AIRC...
Ahmed Momtaz Hosny, PhD
Optimal PID Controller Design for Speed Control of a Separately Excited DC Mo...
Optimal PID Controller Design for Speed Control of a Separately Excited DC Mo...
ijscmcj
Computation of Simple Robust PI/PID Controller Design for Time-Delay Systems ...
Computation of Simple Robust PI/PID Controller Design for Time-Delay Systems ...
IRJET Journal
Performance analysis of a second order system using mrac
Performance analysis of a second order system using mrac
iaemedu
Multi parametric model predictive control based on laguerre model for permane...
Multi parametric model predictive control based on laguerre model for permane...
IJECEIAES
Tuning of PID, SVFB and LQ Controllers Using Genetic Algorithms
Tuning of PID, SVFB and LQ Controllers Using Genetic Algorithms
International Journal of Engineering Inventions www.ijeijournal.com
A comparative study of controllers for stabilizing a rotary inverted pendulum
A comparative study of controllers for stabilizing a rotary inverted pendulum
ijccmsjournal
Multistage condition-monitoring-system-of-aircraft-gas-turbine-engine
Multistage condition-monitoring-system-of-aircraft-gas-turbine-engine
Cemal Ardil
COMBINED ECONOMIC AND EMISSION DISPATCH WITH AND WITHOUT CONSIDERING TRANSMIS...
COMBINED ECONOMIC AND EMISSION DISPATCH WITH AND WITHOUT CONSIDERING TRANSMIS...
cscpconf
Modified sub-gradient based combined objective technique and evolutionary pro...
Modified sub-gradient based combined objective technique and evolutionary pro...
IJECEIAES
Model Reference Adaptation Systems (MRAS)
Model Reference Adaptation Systems (MRAS)
Mohamed Mohamed El-Sayed
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...
IJECEIAES
call for papers, research paper publishing, where to publish research paper, ...
call for papers, research paper publishing, where to publish research paper, ...
International Journal of Engineering Inventions www.ijeijournal.com
Behavioural analysis of a complex manufacturing system having queue in the ma...
Behavioural analysis of a complex manufacturing system having queue in the ma...
Alexander Decker
Fz3410961102
Fz3410961102
IJERA Editor
Control of new 3 d chaotic system
Control of new 3 d chaotic system
Zac Darcy
Computing Inner Eigenvalues of Matrices in Tensor Train Matrix Format
Computing Inner Eigenvalues of Matrices in Tensor Train Matrix Format
Thomas Mach
Adaptive pi based on direct synthesis nishant
Adaptive pi based on direct synthesis nishant
Nishant Parikh
Simultaneous State and Actuator Fault Estimation With Fuzzy Descriptor PMID a...
Simultaneous State and Actuator Fault Estimation With Fuzzy Descriptor PMID a...
Waqas Tariq
Concrete beam with impactor on top
Concrete beam with impactor on top
Vishnu R
Neural Network Control Based on Adaptive Observer for Quadrotor Helicopter
Neural Network Control Based on Adaptive Observer for Quadrotor Helicopter
IJITCA Journal
11.coalfired power plant boiler unit decision support system
11.coalfired power plant boiler unit decision support system
Alexander Decker
Developmental attitude towards science among girls of secondary
Developmental attitude towards science among girls of secondary
IAEME Publication
Comparative analysis of multi stage cordic using micro rotation technique
Comparative analysis of multi stage cordic using micro rotation technique
IAEME Publication
Utilization of bentonite silt mixtures as seepage barriers in liner systems
Utilization of bentonite silt mixtures as seepage barriers in liner systems
IAEME Publication
Optimization of surface roughness in high speed end milling operation using
Optimization of surface roughness in high speed end milling operation using
IAEME Publication
Consumer behaviour a key influencer of rural market potential
Consumer behaviour a key influencer of rural market potential
IAEME Publication
Effect of the welding process parameter in mmaw for joining of dissimilar metals
Effect of the welding process parameter in mmaw for joining of dissimilar metals
IAEME Publication
Simulation and optimization of unloading point of a sugarcane industry
Simulation and optimization of unloading point of a sugarcane industry
IAEME Publication
Mais conteúdo relacionado
Mais procurados
Multistage condition-monitoring-system-of-aircraft-gas-turbine-engine
Multistage condition-monitoring-system-of-aircraft-gas-turbine-engine
Cemal Ardil
COMBINED ECONOMIC AND EMISSION DISPATCH WITH AND WITHOUT CONSIDERING TRANSMIS...
COMBINED ECONOMIC AND EMISSION DISPATCH WITH AND WITHOUT CONSIDERING TRANSMIS...
cscpconf
Modified sub-gradient based combined objective technique and evolutionary pro...
Modified sub-gradient based combined objective technique and evolutionary pro...
IJECEIAES
Model Reference Adaptation Systems (MRAS)
Model Reference Adaptation Systems (MRAS)
Mohamed Mohamed El-Sayed
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...
IJECEIAES
call for papers, research paper publishing, where to publish research paper, ...
call for papers, research paper publishing, where to publish research paper, ...
International Journal of Engineering Inventions www.ijeijournal.com
Behavioural analysis of a complex manufacturing system having queue in the ma...
Behavioural analysis of a complex manufacturing system having queue in the ma...
Alexander Decker
Fz3410961102
Fz3410961102
IJERA Editor
Control of new 3 d chaotic system
Control of new 3 d chaotic system
Zac Darcy
Computing Inner Eigenvalues of Matrices in Tensor Train Matrix Format
Computing Inner Eigenvalues of Matrices in Tensor Train Matrix Format
Thomas Mach
Adaptive pi based on direct synthesis nishant
Adaptive pi based on direct synthesis nishant
Nishant Parikh
Simultaneous State and Actuator Fault Estimation With Fuzzy Descriptor PMID a...
Simultaneous State and Actuator Fault Estimation With Fuzzy Descriptor PMID a...
Waqas Tariq
Concrete beam with impactor on top
Concrete beam with impactor on top
Vishnu R
Neural Network Control Based on Adaptive Observer for Quadrotor Helicopter
Neural Network Control Based on Adaptive Observer for Quadrotor Helicopter
IJITCA Journal
11.coalfired power plant boiler unit decision support system
11.coalfired power plant boiler unit decision support system
Alexander Decker
Mais procurados
(15)
Multistage condition-monitoring-system-of-aircraft-gas-turbine-engine
Multistage condition-monitoring-system-of-aircraft-gas-turbine-engine
COMBINED ECONOMIC AND EMISSION DISPATCH WITH AND WITHOUT CONSIDERING TRANSMIS...
COMBINED ECONOMIC AND EMISSION DISPATCH WITH AND WITHOUT CONSIDERING TRANSMIS...
Modified sub-gradient based combined objective technique and evolutionary pro...
Modified sub-gradient based combined objective technique and evolutionary pro...
Model Reference Adaptation Systems (MRAS)
Model Reference Adaptation Systems (MRAS)
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...
call for papers, research paper publishing, where to publish research paper, ...
call for papers, research paper publishing, where to publish research paper, ...
Behavioural analysis of a complex manufacturing system having queue in the ma...
Behavioural analysis of a complex manufacturing system having queue in the ma...
Fz3410961102
Fz3410961102
Control of new 3 d chaotic system
Control of new 3 d chaotic system
Computing Inner Eigenvalues of Matrices in Tensor Train Matrix Format
Computing Inner Eigenvalues of Matrices in Tensor Train Matrix Format
Adaptive pi based on direct synthesis nishant
Adaptive pi based on direct synthesis nishant
Simultaneous State and Actuator Fault Estimation With Fuzzy Descriptor PMID a...
Simultaneous State and Actuator Fault Estimation With Fuzzy Descriptor PMID a...
Concrete beam with impactor on top
Concrete beam with impactor on top
Neural Network Control Based on Adaptive Observer for Quadrotor Helicopter
Neural Network Control Based on Adaptive Observer for Quadrotor Helicopter
11.coalfired power plant boiler unit decision support system
11.coalfired power plant boiler unit decision support system
Destaque
Developmental attitude towards science among girls of secondary
Developmental attitude towards science among girls of secondary
IAEME Publication
Comparative analysis of multi stage cordic using micro rotation technique
Comparative analysis of multi stage cordic using micro rotation technique
IAEME Publication
Utilization of bentonite silt mixtures as seepage barriers in liner systems
Utilization of bentonite silt mixtures as seepage barriers in liner systems
IAEME Publication
Optimization of surface roughness in high speed end milling operation using
Optimization of surface roughness in high speed end milling operation using
IAEME Publication
Consumer behaviour a key influencer of rural market potential
Consumer behaviour a key influencer of rural market potential
IAEME Publication
Effect of the welding process parameter in mmaw for joining of dissimilar metals
Effect of the welding process parameter in mmaw for joining of dissimilar metals
IAEME Publication
Simulation and optimization of unloading point of a sugarcane industry
Simulation and optimization of unloading point of a sugarcane industry
IAEME Publication
A mathematical model for predicting autoclave expansion for portland cement 2
A mathematical model for predicting autoclave expansion for portland cement 2
IAEME Publication
Analyzing numerically study the effect of add a spacer layer in gires tournois
Analyzing numerically study the effect of add a spacer layer in gires tournois
IAEME Publication
Consideration of reactive energy in the tariff structure
Consideration of reactive energy in the tariff structure
IAEME Publication
Achieving sustainable competitive advantage through resource configur
Achieving sustainable competitive advantage through resource configur
IAEME Publication
Performance and emission study of jatropha biodiesel and its blends
Performance and emission study of jatropha biodiesel and its blends
IAEME Publication
Call for paper july-august 2013
Call for paper july-august 2013
IAEME Publication
The suitability of oxytenanthera abyssinica for development of prostheses in de
The suitability of oxytenanthera abyssinica for development of prostheses in de
IAEME Publication
Optimal dg placement using multiobjective index and its effect on stability 2
Optimal dg placement using multiobjective index and its effect on stability 2
IAEME Publication
Improvement the level of service for signalized arterial 2
Improvement the level of service for signalized arterial 2
IAEME Publication
Comunicato n 3 del 02 11-2011
Comunicato n 3 del 02 11-2011
Olandesi Volanti
42 45
42 45
femmerick
Suenos verano [autoguardado]
Suenos verano [autoguardado]
neoni-00
Dieta dos ossos
Dieta dos ossos
femmerick
Destaque
(20)
Developmental attitude towards science among girls of secondary
Developmental attitude towards science among girls of secondary
Comparative analysis of multi stage cordic using micro rotation technique
Comparative analysis of multi stage cordic using micro rotation technique
Utilization of bentonite silt mixtures as seepage barriers in liner systems
Utilization of bentonite silt mixtures as seepage barriers in liner systems
Optimization of surface roughness in high speed end milling operation using
Optimization of surface roughness in high speed end milling operation using
Consumer behaviour a key influencer of rural market potential
Consumer behaviour a key influencer of rural market potential
Effect of the welding process parameter in mmaw for joining of dissimilar metals
Effect of the welding process parameter in mmaw for joining of dissimilar metals
Simulation and optimization of unloading point of a sugarcane industry
Simulation and optimization of unloading point of a sugarcane industry
A mathematical model for predicting autoclave expansion for portland cement 2
A mathematical model for predicting autoclave expansion for portland cement 2
Analyzing numerically study the effect of add a spacer layer in gires tournois
Analyzing numerically study the effect of add a spacer layer in gires tournois
Consideration of reactive energy in the tariff structure
Consideration of reactive energy in the tariff structure
Achieving sustainable competitive advantage through resource configur
Achieving sustainable competitive advantage through resource configur
Performance and emission study of jatropha biodiesel and its blends
Performance and emission study of jatropha biodiesel and its blends
Call for paper july-august 2013
Call for paper july-august 2013
The suitability of oxytenanthera abyssinica for development of prostheses in de
The suitability of oxytenanthera abyssinica for development of prostheses in de
Optimal dg placement using multiobjective index and its effect on stability 2
Optimal dg placement using multiobjective index and its effect on stability 2
Improvement the level of service for signalized arterial 2
Improvement the level of service for signalized arterial 2
Comunicato n 3 del 02 11-2011
Comunicato n 3 del 02 11-2011
42 45
42 45
Suenos verano [autoguardado]
Suenos verano [autoguardado]
Dieta dos ossos
Dieta dos ossos
Semelhante a Optimum tuning of pid controller for a permanent magnet brushless dc motor
Performance analysis of a second order system using mrac
Performance analysis of a second order system using mrac
IAEME Publication
Design of a novel controller to increase the frequency response of an aerospace
Design of a novel controller to increase the frequency response of an aerospace
IAEME Publication
Fuzzy logic based mrac for a second order system
Fuzzy logic based mrac for a second order system
IAEME Publication
Fuzzy logic based mrac for a second order system
Fuzzy logic based mrac for a second order system
IAEME Publication
Robust model reference adaptive control for a second order system 2
Robust model reference adaptive control for a second order system 2
IAEME Publication
Pso based fractional order automatic generation controller for two area power...
Pso based fractional order automatic generation controller for two area power...
IAEME Publication
30120130406002
30120130406002
IAEME Publication
Robust PID Controller Design for Non-Minimum Phase Systems using Magnitude Op...
Robust PID Controller Design for Non-Minimum Phase Systems using Magnitude Op...
IRJET Journal
Design of Adaptive Sliding Mode Control with Fuzzy Controller and PID Tuning ...
Design of Adaptive Sliding Mode Control with Fuzzy Controller and PID Tuning ...
IRJET Journal
Co36544546
Co36544546
IJERA Editor
12 article azojete vol 8 125 131
12 article azojete vol 8 125 131
Oyeniyi Samuel
Genetic Algorithm for solving Dynamic Supply Chain Problem
Genetic Algorithm for solving Dynamic Supply Chain Problem
AI Publications
Design of multiloop controller for multivariable system using coefficient 2
Design of multiloop controller for multivariable system using coefficient 2
IAEME Publication
Optimal tuning of pid power system stabilizer in simulink environment
Optimal tuning of pid power system stabilizer in simulink environment
IAEME Publication
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...
ijscmcj
30120140505012
30120140505012
IAEME Publication
TUNING OF AN I-PD CONTROLLER USED WITH A HIGHLY OSCILLATING SECOND-ORDER PROC...
TUNING OF AN I-PD CONTROLLER USED WITH A HIGHLY OSCILLATING SECOND-ORDER PROC...
IAEME Publication
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...
ijscmcjournal
Fractional order PID controller tuned by bat algorithm for robot trajectory c...
Fractional order PID controller tuned by bat algorithm for robot trajectory c...
nooriasukmaningtyas
Design of multiloop controller for
Design of multiloop controller for
ijsc
Semelhante a Optimum tuning of pid controller for a permanent magnet brushless dc motor
(20)
Performance analysis of a second order system using mrac
Performance analysis of a second order system using mrac
Design of a novel controller to increase the frequency response of an aerospace
Design of a novel controller to increase the frequency response of an aerospace
Fuzzy logic based mrac for a second order system
Fuzzy logic based mrac for a second order system
Fuzzy logic based mrac for a second order system
Fuzzy logic based mrac for a second order system
Robust model reference adaptive control for a second order system 2
Robust model reference adaptive control for a second order system 2
Pso based fractional order automatic generation controller for two area power...
Pso based fractional order automatic generation controller for two area power...
30120130406002
30120130406002
Robust PID Controller Design for Non-Minimum Phase Systems using Magnitude Op...
Robust PID Controller Design for Non-Minimum Phase Systems using Magnitude Op...
Design of Adaptive Sliding Mode Control with Fuzzy Controller and PID Tuning ...
Design of Adaptive Sliding Mode Control with Fuzzy Controller and PID Tuning ...
Co36544546
Co36544546
12 article azojete vol 8 125 131
12 article azojete vol 8 125 131
Genetic Algorithm for solving Dynamic Supply Chain Problem
Genetic Algorithm for solving Dynamic Supply Chain Problem
Design of multiloop controller for multivariable system using coefficient 2
Design of multiloop controller for multivariable system using coefficient 2
Optimal tuning of pid power system stabilizer in simulink environment
Optimal tuning of pid power system stabilizer in simulink environment
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...
30120140505012
30120140505012
TUNING OF AN I-PD CONTROLLER USED WITH A HIGHLY OSCILLATING SECOND-ORDER PROC...
TUNING OF AN I-PD CONTROLLER USED WITH A HIGHLY OSCILLATING SECOND-ORDER PROC...
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...
Fractional order PID controller tuned by bat algorithm for robot trajectory c...
Fractional order PID controller tuned by bat algorithm for robot trajectory c...
Design of multiloop controller for
Design of multiloop controller for
Mais de IAEME Publication
IAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME Publication
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
IAEME Publication
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
IAEME Publication
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
IAEME Publication
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
IAEME Publication
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
IAEME Publication
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
IAEME Publication
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IAEME Publication
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
IAEME Publication
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
IAEME Publication
GANDHI ON NON-VIOLENT POLICE
GANDHI ON NON-VIOLENT POLICE
IAEME Publication
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
IAEME Publication
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
IAEME Publication
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
IAEME Publication
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
IAEME Publication
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
IAEME Publication
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
IAEME Publication
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
IAEME Publication
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
IAEME Publication
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
IAEME Publication
Mais de IAEME Publication
(20)
IAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME_Publication_Call_for_Paper_September_2022.pdf
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
GANDHI ON NON-VIOLENT POLICE
GANDHI ON NON-VIOLENT POLICE
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
Optimum tuning of pid controller for a permanent magnet brushless dc motor
1.
INTERNATIONAL JOURNAL OF
ELECTRICAL ENGINEERING International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME & TECHNOLOGY (IJEET) ISSN 0976 – 6545(Print) ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), pp. 53-64 IJEET © IAEME: www.iaeme.com/ijeet.asp Journal Impact Factor (2013): 5.5028 (Calculated by GISI) ©IAEME www.jifactor.com OPTIMUM TUNING OF PID CONTROLLER FOR A PERMANENT MAGNET BRUSHLESS DC MOTOR AMGED S. EL-WAKEEL1, F.HASSAN2, A.KAMEL3, A.ABDEL-HAMED3 1 Military Technical College, 2 Helwan University, 3 High Institute of Engineering, El Shorouk Academy ABSTRACT The proportional-integral-derivative (PID) controllers were the most popular controllers of this century because of their remarkable effectiveness, simplicity of implementation and broad applicability. However, PID controllers are poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. The computational intelligence has purposed genetic algorithms (GA) and particle swarm optimization (PSO) as opened paths to a new generation of advanced process control. The main objective of these techniques is to design an industrial control system able to achieve optimal performance when facing variable types of disturbances which are unknown in most practical applications. This paper presents a comparison study of using two algorithms for the tuning of PID-controllers for speed control of a Permanent Magnet Brushless DC (BLDC) Motor. The PSO has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The BLDC Motor is modelled using system identification toolbox. Comparing GA with PSO method proves that the PSO was more efficient in improving the step response characteristics. Experimental results have been investigated to show their agreement with simulation one. Keywords: Permanent Magnet Brushless DC (BLDC) Motor, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), PID Controller, and Optimal control. 53
2.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 1. INTRODUCTION The usefulness of PID controllers lies in their general applicability to most control systems. The PID controller is a combination of PI and PD controllers. It is a lag-lead-lead compensator. Note that the PI control and PD control actions occur in different frequency regions. The PI control action occurs at the low-frequency region and the PD control action occurs at the high-frequency region. The PID control may be used when the system requires improvement in both transient and steady-state performances Figure 1 shows a PID control of a plant G(s). If the mathematical model of the plant can be derived, then it is possible to apply various design techniques for determining the parameters of the controller that will meet the transient and steady-state specifications of the closed loop system. Ziegler and Nichols suggested rules for tuning PID controllers based on experimental step responses in process control system where the plant dynamics are precisely known. Over many years such tuning techniques proved to be useful. In order to optimize the PID controller parameters, the PSO and GA have been used to optimize PID parameters. PSO shares many similarities with evolutionary computation techniques such as GA. the performance of the BLDC Motor with the PID controller tuned by GA is compared with the same controller tuned by PSO using different objective functions [1], [2], [3]. Kp + Y (s ) + R(s) E (s ) G (s ) Ki S + - + Plant Kd S Controller Figure 1: PID Controlled System. This paper is restricted for considering the two aforementioned optimization algorithms, PSO and GA, for tuning the gains of PID controllers that is used with the BLDC Motor. This is done by presenting some results obtained by using each algorithm individually. These results are compared and relative merits of these algorithms are discussed. 2. SYSTEM MODELLING 2.1. PID Controller and Fitness Function Modelling The PID controller has been widely adopted as the control strategy in the production process. Basically, a proportional-plus-integral-plus-derivative (PID) controller will improve the speed of the response, the steady-state error, and the system stability. However, the 54
3.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME setting of PID parameters is related to the characters of system process. Thus, the proper or optimum PID parameters are needed to approach the desired performance. The transfer function of a PID controller is [1]. Kd Gc ( s ) = K p + + Kd S (1) S The strategies of PSO and GA are implemented for the optimum search of the controller parameters. These done according to the criteria of performance index, i.e., IAE (Integral Absolute-Error), ISE (Integral Square-Error), ITAE (Integral of Time multiplied by Absolute Error), WGAM1 (Weighted Goal Attainment Method 1), and WGAM2 (Weighted goal attainment method 2 (WGA2).The three integral performance criteria in the frequency domain have their own advantages and disadvantages [4]. The IAE, ISE, ITSE, WGAM1, and WGAM2 performance criterion formulas are described by equations 2, 4, 5, 6, and 7 respectively. ∞ ∞ IAE = ∫ r (t ) − y(t ) dt = ∫ e(t ) dt (2) 0 0 Then the fitness function (f) to be maximized using IAE is given by equation (3). 1 f = (3) IAE ∞ ISE = ∫ [e(t )] 2 dt (4) 0 ∞ ITAE = ∫ t e(t ) dt (5) 0 1 WGAM 1 = (6) [c1 (t r − t rd ) 2 + c 2 ( M p − M pd ) + c3 (t s − t sd ) 2 + c4 (ess − essd ) 2 ] 2 1 WGAM 2 = (7) (1 − e ) ⋅ ( M p + ess ) + (e − β ) ⋅ (t s − t r ) −β Where, r(t) is the desired output, y(t) is the plant output, e(t) is the error signal, β weighting factor, c1 : c 4 are positive constants (weighting factor), their values are chosen according to prioritizing their importance, t rd is the desired rise time, M pd is the desired maximum overshoot, t sd is the desired settling time, and e ssd is the desired steady state error. 55
4.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 2.2. Permanent Magnet Brushless DC Motor Modelling In this section, system identification toolbox in MATLAB used to find the transfer function of the motor and its drive circuit. The state space models are estimated for orders ranging from 1 to 5 (na=1:5) using descending step input voltage data (5-2 V) and its related output as a test data. The same set of data is used as a validation data and time delay of 0.03 sec for all models. Figure (2) shows the measured output and the percentage fit of each model to the measured output. It is clear from figure (2) that the best fitting for the validation data set is obtained for state space model of order three (94.08%) [5]. Then, the transfer function of the motor and its drive circuit is indicated in equation 8, the closed loop system is as shown in Figure (3). 312.3S + 1.7774e4 G p (S ) = (8) S 2 + 10.2 S + 54.32 Measured and simulated model output 2000 na=5 92.98% 1800 na=4 92.84% na=3 92.26% 1600 na=2 94.08% na=1 83.77% 1400 BEST FITS 1200 Speed (rpm) 1000 800 600 400 200 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Time (sec) Figure 2: Measured and simulated state space model output GA or PSO Tuning ω r (s) E (s ) 312.3S + 1.7774e4 ω a (s) Ki Kp + + Kd S Gc ( S ) = S S 2 + 10.2 S + 54.32 Figure 3: The structure of GA or PSO of PID tuning system. 56
5.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 2.3. Modelling of the PSO-PID Controller In this section, the PSO-PID controller is proposed. The method of tuning the parameters of PID controller by the PSO is studied. The operation algorithm is based on the local and global best solution as the following equations [1], [2]. vik +1 = wi vik + c1 randx ( pbest i − s ik ) + c 2 rand ( gbest − s ik ) (9) Where, v ik is the current velocity of particle i at iteration k , vik +1 is the updated velocity of particle i, wi is the different inertia weight of particle i, c1 and c 2 are acceleration positive constants, s ik is the current position of particle i at iteration k, rand is random number between 0 and 1, pbest i is the best previous position of the i-th particle, and gbest is the best particle among all the particles in the population. Therefore the new position can be modified using the present position and updated velocity as in the next equation. s ik +1 = s ik + v ik +1 (10) The acceleration positive constants c1 and c 2 are set to 2 [6]. The inertia weight wi is set within the range (0.4 to 0.9) [7], [8]. 2.4. Modelling of the GA-PID Controller In this section, the GA-PID controller is proposed for comparison. The parameters of PID controller are tuned by the GA. In nature, evolution is mostly determined by natural selection, where individuals that are better are more likely to survive and propagate their genetic material. The encoding of genetic information (genome) is done in a way that admits reproduction which results in offspring or children that are genetically identical to the parent. Reproduction allows some exchange and re-ordering of chromosomes, producing offspring that contain a combination of information from each parent. This is the recombination operation, which is often referred to as crossover because of the way strands of chromosomes crossover during the exchange. Diversity in the population is achieved by mutation. A typical GA procedure takes the following steps: A population of candidate solutions (for the optimization task to be solved) is initialized. New solutions are created by applying genetic operators (mutation and crossover). The fitness of the resulting solutions is evaluated and suitable selection strategy is then applied to determine which solutions will be maintained into the next generation. The procedure is then iterated until a terminating criterion is achieved [1], [9]. 3. SIMULATION AND EXPERIMENTAL RESULTS 3.1. Simulation Results In the simulation, the optimum PID parameters are searched for the transfer function of the identified model with respect to the criteria of performance indices presented in equations 2, 4, 5, 6 and 7. The GAM1 searched for case1 ( t rd = 0.3, c1 =1 and c 2 = c 3 = c 4 = 0 ) and case3 ( M p = 0, 57
6.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME t rd = 0.3, c1 =0.1, c 2 = 0.9 and c 3 = c 4 = 0). The GAM2 searched for case1 ( β = 0.1 ) and case2 ( β = 0.7 ).The efforts of the identified model with the PSO and GA controllers are collected in. Table1. In addition, the time responses are shown in Figures 4, 5, and 6. Table 1: The efforts of the PSO and GA for PID controllers in simulation w.r.t. w.r.t. w.r.t. w.r.t. w.r.t. response Tunin IAE &P,I,D g ISE ITAE WGAM1 WGAM2 values metho Case1 Case2 Case1 Case2 ds value of GA 3.9489 13.311 17.13 4.4e3 1.1e+0 2.6753 9.9592 fitness 0 50 4 function PSO 3.9512 13.309 21.47 4.4e3 1.6e+0 6.8187 11.3544 9 43 4 seeking GA 271 266 352 390 410 390 380 time(sec PSO 94 67 140 240 249 286 265 ) rising GA 0.1400 0.1400 0.42 0.315 0.33 0.350 0.395 time(sec PSO 0.1400 0.1400 0.415 0.3150 0.3250 0.520 0.53 ) overshot GA 0.4104 0.31 2.430 20.81 0 2.9543 1.2034 percenta 1 ge PSO 0 0.2955 0.269 19.254 0 1.9783 0.7255 7 9 settling GA 2.350 2.355 1 1.96 1.235 0.76 0.585 time PSO 2.350 2.355 0.645 1.5350 1.2200 0.520 0.53 (sec) Steady- GA 0. 22 0. 22 7.74e- - 6.434e 5.1810e- 2.5883e- state 8 0.0038 -4 6 9 error PSO 0.2156 0.2170 2.50e- 0.0012 0 2.306e- 1.1541e- 7 06 7 P GA 0.0090 0.009 0.002 1.9949 0.0027 0.0012 0.0018 e-5 PSO 0.0090 0.009 0.002 0.0000 0.0027 0.00128 0.00143 3 9 24 99 I GA 0.012 0.012 0.012 0.012 0.0119 0.012 0.012 PSO 0.012 0.012 0.012 0.012 0.012 0.01192 0.01197 3 9 D GA 0 2.7785 3.220e 6.764e 6.0274 4.6979e- 5.371e-5 e-6 -4 -6 e-6 5 PSO 1.3171 3.2151 3.027e 0 0 4.0973e- 2.0459e- e-5 e-6 -4 5 4 58
7.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME GA 1 PSO 0.8 Speed(rpm) 0.6 0.4 0.2 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Time(sec) Figure 4: Simulation with respect to ITAE GA PSO 1.2 1.1 Speed(rpm) 1 0.9 0.8 0.7 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Time(sec) Figure 5: Simulation with respect to WGAM1case1 1.1 GA 1.05 PSO 1 0.95 Speed(rpm) 0.9 0.85 0.8 0.75 0.7 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Time(sec) Figure 6: Simulation with respect to WGAM2 (case2) 59
8.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 3.2. Experimental results The experiment was set up as shown in Figure (13). The parameters of tested BLDC Motor are listed in table (2). A data acquisition card (NI6014) was utilized as a control core responsible for the system control. The optimum PID controller tuned by GA and PSO using ITAE index is applied to closed-loop control of BLDC motor and its drive circuit. The experimental results of the practical system are compared with the simulation results of the same system under the influence of the same controller. Figure (7) illustrates the practical BLDC motor and the corresponding identified model performance with optimum PID controller tuned by PSO using the ITAE fitness function. Table (3) summarizes the steady state response of the practical BLDC motor and the corresponding identified model. It is clear from figure (7) and table (2) that the practical motor behaves like the identified model but the remarkable difference in the overshot is due to the ripples in the output signal from the practical model. The time responses of GA-PID and PSO-PID in the practical system are shown in Figures (8). Obviously, the PSO-PID controller has better performance and efficiency than the GA- PID controller. Table 2: The parameters of Tested BLDC Motor Power 370 W Armature inductance (La ) 8.5 mH Speed 2000 rpm Moment of inertia (J ) 0.0008 kg.m2 Voltage 220 V Coefficient of friction (B) 0.0003 N.m.sec/rad Number of poles 4 EMF constant (Kb ) 0.175 V.sec Armature resistance (Ra ) 2.8750 2500 identified model, Practical system practical system 2000 Identified model 1500 speed (rpm) 1000 500 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 time (sec) Figure 7: The speed response of practical motor and the identified model Table 3: The steady-state response parameters using PSO-PID Parameter Actual System Identified Model Maximum over shoot Mp% 2.0813% 0.2711% Settling time Ts(sec) 0.515sec 0.5600sec Rise time Tr(sec) 0.3800sec 0.4150 sec Steady state error ess% 0.0854% 1.5488e-004 60
9.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 2500 GA GA, PSO 2000 PSO 1500 speed (rpm) 1000 500 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 time (sec) Figure 8: Experiment with respect to ITAE Figures 9 and 10 illustrate the actual system and its identified model performance to maintain speed of multi-step set point with optimum PID controller tuned by GA and PSO respectively using (ITAE) fitness function. 2500 reference signal Reference identified model practical system 2000 1500 speed(rpm) Identified model 1000 500 Practical System 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 time(sec) Figure 9: The speed response of multi-step speeds using GA-PID 61
10.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 2500 reference signal identified model Reference practical system 2000 1500 Identified Model speed(rpm) 1000 Practical System 500 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 time(sec) Figure 10: The speed response of multi-step speeds using PSO-PID 3.3. Motor Loading Figure (11) shows the actual system speed response to maintain speed 2000 rpm with sudden load (1.2N.m) applied after 2 seconds with no feedback (open loop). It is clear that the speed decreases, and no recovery occurs. Figure (12) illustrates the actual system speed response with optimum PID controller tuned by GA and PSO techniques using ITAE fitness function. Clearly, the recovery time in case of PSO is smaller than that of GA. 2500 2000 1500 speed(rpm) 1000 500 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 time(sec) Figure 11: The speed response in open loop control 62
11.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 2200 PSO GA PSO 2000 1800 Speed(rpm) GA 1600 1400 1200 1000 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Time(sec) Figure 12: The speed response using (ITAE) Drive Circuit PID Control PM. Brushless Motor Tachometer Load Figure 13: The experiment setup 4. CONCLUSIONS The transfer function of the BLDC Motor and its Drive Circuit is derived using system identification technique. The optimization of BLDC Motor Drive controller parameters was derived thought GA and PSO algorithms. Simulation and experimental results proved that the PSO is more efficient than the genetic algorithm in seeking for the global optimum PID parameters with respect to the desired performance indices. Thus, the system performs better time response with the optimum PID controller. In addition, the PSO algorithm is easier to implement than the GA. 63
12.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 5. REFERENCES [1] Chen, and Shih-Feng. '' Particle Swarm Optimization for PID Controllers with Robust Testing''. s.l. : International Conference on Machine Learning and Cybernetics, 19-22 Aug. 2007. pp. 956 – 961. [2] Haibing Hu, Qingbo Hu, Zhengyu Lu, and Dehong Xu. '' Optimal PID Controller Design in PMSM Servo System Via Particle Swarm Optimization''. s.l. : Annual conference of IEEE on Industrial Electronic Society, Zhejiang University,China, 6-10 Nov. 2005. pp. 79 – 83. [3] Mohammed El-Said El-Telbany. '' Employing Particle Swarm Optimizer and Genetic Algorithms for Optimal Tuning of PID Controllers: A Comparative Study''. s.l. : ICGST-ACSE Journal, Volume 7, Issue 2, November 2007. [4] Mehdi Nasri, Hossein Nezamabadi-pour, and Malihe Maghfoori. ''A PSO-Based Optimum Design of PID Controller fora Linear Brushless DC Motor''. s.l. : Proceeding of World Academy of Science on Engineering and Technology, 20 April 2007. pp. 211-215. [5] Lennart Ljung. “System Identification Toolbox 7.3: User’s Guide”. s.l. : MathWorks Inc., 2009. [6] James Kennedy, and Russell Eberhart. "Particle Swarm Optimization". s.l. : IEEE Int. Conf.Evol. Neural Network. Perth, Australia, 2005. pp. 1942-1948. [7] Gaing, Zwe-Lee. "A Particle Swarm Optimization Approach for Optimum Design of PID Controller in AVR System". s.l. : IEEE Tran. Energy Conversion, Vol.19(2), Jun. 2004. pp. 384- 391. [8] Yuhui Shi, and Russell Eberhart. "A Modified Particle Swarm Optimizer". s.l. : IEEE int. Conf. Evol.Comput,Indiana Univ., Indianapolis, IN. pp. 69-73. [9] Dong Hwa Kim, Ajith Abraham, and Jae Hoon Cho. '' A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Global Optimization'‘. s.l. : Information Sciences 177, (2007). pp. 3918–3937. [10] VenkataRamesh.Edara, B.Amarendra Reddy, Srikanth Monangi, and M.Vimala, “Analytical Structures For Fuzzy PID Controllers and Applications” International Journal of Electrical Engineering & Technology (IJEET), Volume 1, Issue 1, 2010, pp. 1 - 17, ISSN Print : 0976-6545, ISSN Online: 0976-6553 Published by IAEME 6. LIST OF SYMBOLS PID Proportional-plus-Integral-plus-Derivative PSO Particle Swarm Optimization GA Genetic Algorithm Kp Proportional Gain Ki Integral Gain Kd Derivative Gain IAE Integral Absolute Error ISE Integral Square Error ITAE Integral of Time multiplied by Absolute Error WGAM Weighted Goal Attainment Method r(t) Desired input y(t) Plant output M pd Desired maximum overshot t sd Desired settling time essd Desired steady-state error t rd Desired rise-time 64
Baixar agora