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Design of Multi-objective Evolutionary Technique Based Intelligent Controller for Multivariable Nonlinear Systems

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Artificial Intelligence and Soft Computing - ICAISC 2004 (ICAISC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3070))

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Abstract

The main objective of this paper is to present a new method based on Multiobjective evolutionary algorithm for control of the multivariable and nonlinear systems. Problem design considers time domain specifications such as overshoot, rising time, settling time and stationary error as well as interaction effects. Genetic algorithms are employed to satisfy time domain design specifications, that are not considered in an explicit way in the standard nonlinear control theory. Adaptation, setpoint tracking and satisfaction of temporary response specifications are the advantages of this method that be shown by some simulations.

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References

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Author information

Authors and Affiliations

  1. Control Research Department, Engineering Research Institute, Tehran, Iran, P.O.Box: 13445-754, Tehran

    Farzan Rashidi

  2. Hormozgan Regional Electric Co., Bandar-Abbas, Iran

    Mehran Rashidi

Authors
  1. Farzan Rashidi
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  2. Mehran Rashidi
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. German Research Center of Artificial Intelligence (DFKI), Germany

    Jörg H. Siekmann

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA

    Lotfi A. Zadeh

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© 2004 Springer-Verlag Berlin Heidelberg

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Rashidi, F., Rashidi, M. (2004). Design of Multi-objective Evolutionary Technique Based Intelligent Controller for Multivariable Nonlinear Systems. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_152

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  • DOI: https://doi.org/10.1007/978-3-540-24844-6_152

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22123-4

  • Online ISBN: 978-3-540-24844-6

  • eBook Packages: Springer Book Archive

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