In this paper, an adaptive fuzzy controller design methodology via multi-objective particle swarm optimization (MOPSO) based on robust stability criterion is proposed. The plant to be controlled is modeled from its input–output experimental data considering a Takagi–Sugeno (TS) fuzzy nonlinear autoregressive with exogenous input model, by using the fuzzy C-means clustering algorithm (antecedent parameters estimation) and the weighted recursive least squares (WRLS) algorithm (consequent parameters estimation). An adaptation mechanism as MOPSO problem for online tuning of a fuzzy model based digital proportional-integral-derivative (PID) controller parameters, based on the gain and phase margins specifications, is formulated. Experimental results for adaptive fuzzy digital PID control of a thermal plant with time-varying delay are presented to illustrate the efficiency and applicability of the proposed methodology.
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July 2017
Research-Article
Self-Tuning Robust Fuzzy Controller Design Based on Multi-Objective Particle Swarm Optimization Adaptation Mechanism
Edson B. M. Costa,
Edson B. M. Costa
Federal Institute of Education, Science
and Technology,
Department of Electrical Engineering,
Laboratory of Computational Intelligence
and Control - LaCInCo,
Avenue Newton Bello, s/n, Vila Maria,
Imperatriz, CEP 65919-050, Maranhão, Brazil
e-mail: edson.costa@ifma.edu.br
and Technology,
Department of Electrical Engineering,
Laboratory of Computational Intelligence
and Control - LaCInCo,
Avenue Newton Bello, s/n, Vila Maria,
Imperatriz, CEP 65919-050, Maranhão, Brazil
e-mail: edson.costa@ifma.edu.br
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Ginalber L. O. Serra
Ginalber L. O. Serra
Federal Institute of Education, Science
and Technology,
Department of Electroelectronics,
Laboratory of Computational Intelligence Applied
to Technology,
Avenue Getúlio Vargas, 04, Monte Castelo,
São Luís CEP 65030-005, Maranhão, Brazil
e-mail: ginalber@ifma.edu.br
and Technology,
Department of Electroelectronics,
Laboratory of Computational Intelligence Applied
to Technology,
Avenue Getúlio Vargas, 04, Monte Castelo,
São Luís CEP 65030-005, Maranhão, Brazil
e-mail: ginalber@ifma.edu.br
Search for other works by this author on:
Edson B. M. Costa
Federal Institute of Education, Science
and Technology,
Department of Electrical Engineering,
Laboratory of Computational Intelligence
and Control - LaCInCo,
Avenue Newton Bello, s/n, Vila Maria,
Imperatriz, CEP 65919-050, Maranhão, Brazil
e-mail: edson.costa@ifma.edu.br
and Technology,
Department of Electrical Engineering,
Laboratory of Computational Intelligence
and Control - LaCInCo,
Avenue Newton Bello, s/n, Vila Maria,
Imperatriz, CEP 65919-050, Maranhão, Brazil
e-mail: edson.costa@ifma.edu.br
Ginalber L. O. Serra
Federal Institute of Education, Science
and Technology,
Department of Electroelectronics,
Laboratory of Computational Intelligence Applied
to Technology,
Avenue Getúlio Vargas, 04, Monte Castelo,
São Luís CEP 65030-005, Maranhão, Brazil
e-mail: ginalber@ifma.edu.br
and Technology,
Department of Electroelectronics,
Laboratory of Computational Intelligence Applied
to Technology,
Avenue Getúlio Vargas, 04, Monte Castelo,
São Luís CEP 65030-005, Maranhão, Brazil
e-mail: ginalber@ifma.edu.br
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received January 25, 2016; final manuscript received January 9, 2017; published online May 12, 2017. Assoc. Editor: Srinivasa M. Salapaka.
J. Dyn. Sys., Meas., Control. Jul 2017, 139(7): 071009 (12 pages)
Published Online: May 12, 2017
Article history
Received:
January 25, 2016
Revised:
January 9, 2017
Citation
Costa, E. B. M., and Serra, G. L. O. (May 12, 2017). "Self-Tuning Robust Fuzzy Controller Design Based on Multi-Objective Particle Swarm Optimization Adaptation Mechanism." ASME. J. Dyn. Sys., Meas., Control. July 2017; 139(7): 071009. https://doi.org/10.1115/1.4035758
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