Design of a fractional order PID controller for an AVR using particle swarm optimization

Zamani, Majid; Karimi-Ghartemani, Masoud; Sadati, N.; Parniani, Mostafa

doi:10.1016/j.conengprac.2009.07.005

Cited by 569 publications

(309 citation statements)

References 15 publications

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“…For fair comparison of results, maximum number of function evaluations (Fevalmax) is selected as that of [13] for Test system-I. Original MATLAB codes for CMAES algorithm is taken from the website [16]. CMAES algorithm is applied to the design of decoupled multivariable FO-PI controller for Test system-I using IAE as objective.…”

Section: Simulation Resultsmentioning

confidence: 99%

Design Of Multivariable Fractional Order Pid Controller Using Covariance Matrix Adaptation Evolution Strategy

Sivananaithaperumal¹,

Baskar²

2014

Archives of Control Sciences

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Section: Simulation Resultsmentioning

confidence: 99%

Design Of Multivariable Fractional Order Pid Controller Using Covariance Matrix Adaptation Evolution Strategy

Sivananaithaperumal¹,

Baskar²

2014

Archives of Control Sciences

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“…The method is proved to be robust in solving problems featuring nonlinearity and non-differentiability, multiple optima, and high dimensionality. The advantages of the PSO are its relative simplicity and stable convergence characteristic with good computational efficiency [23]. Also PSO has advantages over GA; PSO has faster execution time than GA because it has only one operator; velocity calculation.…”

Section: Controlling Of Chemical Processes (Which Are Basically Multimentioning

confidence: 99%

An Intelligent Control System Design for an Evaporator based on Particle Swarm Optimization

Abdel-Halim¹,

Othman²,

Sakr³

et al. 2017

IJCA

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The main contribution of this paper is aimed to design and implementation of an intelligent level controller and intelligent 2×2 decentralized PI controller and a lead compensator for the forced circulation evaporator by using PSO strategy. The most important thing to guarantee the safe operation of the forced circulation evaporator, without damaging the installed equipment, is obtaining optimal controllers for the evaporator operating pressure and the level of liquid inside the separator part. Also the percent of the concentration of the non-volatile in the solution must be effectively controlled to required limits. PSO algorithm is implemented in MATLAB and is compared to GA strategy for design and implementation of optimal controllers for the evaporator system by minimizing the summation of the characteristics of unit step response. Also computer simulation results are compared to the different two cost functions methods by analyzing the performance, stability and robustness with respect to variation of the evaporator control system.

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“…In 26 parameters of a FO controller were optimized using modified PSO that has better solution and faster search speed in contrast with GA. By using PSO in 27 , a FOPID controller was designed that has remarkable reduction in overshoot, rise time and setting time. In another approach, the PSO was applied to determine FOPID parameters with efficient search and more robust performance using for an automatic voltage regulator 28 . A novel Adaptive PSO was also used in 29 to find optimal parameters of PID controller and unstable nonlinear system.…”

Section: Related Workmentioning

confidence: 99%

Two-link Robot Manipulator using Fractional Order PID Controllers Optimized by Evolutionary Algorithms

Fani¹,

Shahraki²

2016

Biosci., Biotech. Res. Asia

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Fractional order (FO) controllers are highly considered with regard to higher performance and robustness of these controllers in FO systems. According to advantages of PID controllers such as suitable performance, low price and simplicity of design, they are widely used in industry. A FOPID controller is used for two-link robot control in this paper. Considering vast use of evolutionary algorithms and numerical optimization, coefficients of the FO controller are optimized using evolutionary algorithms in this paper. An individual FOPID controller is applied in order to control each link. Three evolutionary optimization algorithms including particle swarm optimization (PSO), genetic algorithm and estimation of distribution algorithm, are compared from optimal coefficients determination point of view. Experimental results indicate that FOPID controller is more applicable according to use of actual model for robot and suitable performance of the PSO algorithm. Key words: Evolutionary algorithms, fractional order controller, PID controller, two-link robotAlong with introduction of fractional order (FO) controllers and their higher performance and robustness on FO systems by Podlubny in 1994, FO systems and their control process are significantly considered 1 . Although PID controllers are introduced long time ago, they are widely used in industry because of their advantages such as low price, design simplicity and suitable performance 2, 3 . While three parameters of design including proportional (K p ), integral (K i ), and derivative (K d ) are available in PID controllers, two more parameters exist in FOPID controllers for adjustment. These parameters are integral fractional order and derivative fractional order 4 . In comparison with PID controllers, FOPID controllers have more flexible design that result in more precise adjustment of closed-loop system 5 . FOPID controllers are defined by FO differential equations. It is possible to tune frequency response of the control system by expanding integral and derivative terms of the PID controller to fractional order case. This characteristic result in a more robust design of control system, but it is not easily possible 6 .According to non-linearity, uncertainty, and confusion behaviors of robot arms, they are highly recommended for experimenting designs of control systems. Despite non-linear behavior of robot arm, it is demonstrable that a linear proportional derivative controller can stabilize the system using Lyapanov 7 . But, classic PD controller itself cannot control robot to reach suitable condition. Several papers and wide researches in optimizing performance of the robot manipulator show the importance of this issue. Different adaptive and robust procedures are proposed for robot control that all of them are so complicated in analysis and design [8][9][10][11] . Approaches that have been proposed for robot control are categorized in non-

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Design of a fractional order PID controller for an AVR using particle swarm optimization

Cited by 569 publications

References 15 publications

Design Of Multivariable Fractional Order Pid Controller Using Covariance Matrix Adaptation Evolution Strategy

Design Of Multivariable Fractional Order Pid Controller Using Covariance Matrix Adaptation Evolution Strategy

An Intelligent Control System Design for an Evaporator based on Particle Swarm Optimization

Two-link Robot Manipulator using Fractional Order PID Controllers Optimized by Evolutionary Algorithms

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