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Strengthening Links Between Data Analysis and Soft Computing pp 273–281Cite as

Multistage Fuzzy Control of a Stochastic System Using a Bacterial Genetic Algorithm

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 315))

Abstract

We consider multistage control problem under fuzzy constraints on controls applied and fuzzy goals on states attained, with a stochastic system under control (a Markov chain). We seek an optimal sequence of controls which maximizes the probability of attaining the fuzzy goal subject to the fuzzy constraints, over a finite, fixed and specified planning horizon. We present an extension of Kacprzyk’s [10, 12] approach, based on a traditional genetic algorithm, by employing a bacterial evolutionary algorithm in the setting of Nawa and Furuhashi [18]. We show that it yields an improved efficiency, and potentials for future extensions.

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Authors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01–447, Warsaw, Poland

    Janusz Kacprzyk

Authors
  1. Janusz Kacprzyk
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Correspondence to Janusz Kacprzyk .

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Editors and Affiliations

  1. Polish Academy of Sciences, Faculty of Mathematics and Information Sciences, Systems Research Institute and Warsaw University of Technology, Warsaw, Poland

    Przemyslaw Grzegorzewski

  2. Polish Academy of Sciences, Faculty of Mathematics and Information Sciences, Systems Research Institute and Warsaw University of Technology, Warsaw, Poland

    Marek Gagolewski

  3. Polish Academy of Sciences Systems Research Institute, Warsaw, Poland

    Olgierd Hryniewicz

  4. Departamento de Estadistica e I.O. y D.M., University of Oviedo, Oviedo, Spain

    María Ángeles Gil

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Kacprzyk, J. (2015). Multistage Fuzzy Control of a Stochastic System Using a Bacterial Genetic Algorithm. In: Grzegorzewski, P., Gagolewski, M., Hryniewicz, O., Gil, M. (eds) Strengthening Links Between Data Analysis and Soft Computing. Advances in Intelligent Systems and Computing, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-319-10765-3_32

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  • DOI: https://doi.org/10.1007/978-3-319-10765-3_32

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10764-6

  • Online ISBN: 978-3-319-10765-3

  • eBook Packages: EngineeringEngineering (R0)

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