Fractional-order PID controller optimization via improved electromagnetism-like algorithm

Lee, Ching‐Hung; Chang, Fu‐Min

doi:10.1016/j.eswa.2010.06.009

Cited by 143 publications

(76 citation statements)

References 25 publications

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“…En este sentido se ha intentado aplicar diferentes técnicas para la sintonización de controles fraccionales, como el método ZieglerNichols [40][41], series de polinomios [42], algoritmos genéticos [43], enjambres de partículas [44], teoría electromagnética [45], cuantificadores dinámicos [46] y modos deslizantes [47] [48]. Sin embargo, muchas de las técnicas usadas presentan problemas por la cantidad de parámetros que se requiere calcular, lo que se traduce en alta carga computacional y altos tiempos de procesamiento, siendo esta la razón de que muchos trabajos de implementación del control fraccional se hayan hecho sobre variables o procesos de reacción lenta, tales como el control de temperatura.…”

Section: Introductionunclassified

Control PID tipo fraccional para la posición del cabezal de una unidad de CD para aplicaciones en microscopia óptica

Valencia¹,

Cardona²

2012

Iteckne

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Resumen-En este artículo se diseña un control PID tipo fraccional para la posición del cabezal de una unidad de CD que se piensa emplear en el desarrollo de un microscopio óptico motorizado. En dicha aplicación se reemplazará el disco o CD por una placa con la muestra que va a ser estudiada, y se usará el cabezal de la unidad para iluminar la muestra. Con el controlador diseñado se busca que no haya dependencia del subcó-digo escrito en un CD para determinar la posición del cabezal, para lo cual se usará un ratón de computador como sensor de posición. También se busca un control que mejore el desempeño del sistema y que sea robusto frente a las incertidumbres en el modelo de la planta, razón por la cual se empleará un control tipo fraccional (PI^λD^μ) y se ajustarán los parámetros K_p, K_i, K_d, λ, μ con cinco especificaciones de robustez. Para la sintonización del control se utiliza la toolbox de optimización de Matlab con la función fmincon. Al final del artículo se presentan los resultados en simulación, se concluye sobre la resolución obtenida, la robustez del controlador y la viabilidad del sistema de control para ser empleado en un microscopio.Palabras clave-Control de posición, Control Fraccional, Control Robusto, Microscopía óptica, ratón óptico, unidad de CD.Abstract-On this work a fractional PID controller is designed for a CD pickup head position control that is intended to use in the development of a motorized optical microscope. In such an application the disk or CD would be replaced by a plate with the sample to be studied, and the pickup head would be used to illuminate the sample. The controller is designed in such a way that there is no dependence on a CD written subcode to determine the position of the head, and for this, a computer mouse is used as a position sensor. We also look for the controller to improve the system performance and to be robust against model uncertainties of the plant, that is why we use a fractional controller PI^λ D^μ and adjust the parameters K_p, K_i, K_dλ and μ according to five robustness rules. For tuning the control we use the Matlab optimization toolbox together with fmincon function. At the end of the paper we present the simulation results, concluding about the resolution obtained, the robustness of the controller and the viability of the control system to be used in a microscope.

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Section: Introductionunclassified

Control PID tipo fraccional para la posición del cabezal de una unidad de CD para aplicaciones en microscopia óptica

Valencia¹,

Cardona²

2012

Iteckne

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“…Another optimal FOPID controller was proposed in 18 for a full vehicle non-linear active suspension system. An electromagnetism-like algorithm and GA based FOPID design is proposed in 19 for second order system with time delay. Proposed algorithm has faster convergence and better global optimization capability.…”

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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“…Last two decades, however, it becomes widespread to utilize by favour of the computers and microprocessors which allow to make simpler estimating of fractional calculus. Analyzing the nature, most of the systems cannot fully identify with the integer derivative & integral terms [4]- [7], on the score of the fact that this result obliges us to define the systems with fractional terms. In this point, fractional calculus is the very key for describing systems which have non-integer derivative and integral terms.…”

Section: Introductionmentioning

confidence: 99%

“…Artificial intelligence (AI) techniques such as fuzzy systems, evolutionary and heuristic algorithms are mostly used obtaining the parameters in the control systems [8], [9]. They present effective conclusion for obtaining optimal points of problems by using numerical solution.…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison of Fractional Controllers and Artificial Intelligence Techniques

Korkmaz¹,

Aydoğdu²

2013

IJMLC

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Abstract-Studying and applications of fractional PIDs (FO-PID) are getting popular for controlling the systems, properly. With this idea, it is aimed to unveil the advantages of FO-PID over traditional integer order PIDs (IO-PID). At the same time, in this paper, artificial intelligence techniques which are particle swarm optimization and genetic algorithm are used to determine which one have more effectiveness and to find system best parameters for both controllers. Results prove the supremacy of FO-PID controllers and PSO algorithm.

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Fractional-order PID controller optimization via improved electromagnetism-like algorithm

Cited by 143 publications

References 25 publications

Control PID tipo fraccional para la posición del cabezal de una unidad de CD para aplicaciones en microscopia óptica

Control PID tipo fraccional para la posición del cabezal de una unidad de CD para aplicaciones en microscopia óptica

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

Performance Comparison of Fractional Controllers and Artificial Intelligence Techniques

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