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Fuzzy Model Based Predictive Controller

  • Chapter
Methods and Applications of Intelligent Control

Part of the book series: Microprocessor-Based and Intelligent Systems Engineering ((ISCA,volume 16))

Abstract

This paper presents a technique in order to identify a fuzzy model which is suitable for fuzzy control of a dynamic system. The basic motivation is to develop a fuzzy controller which makes explicit use of the system dynamics expressed in terms of a set of rules. The fuzzy process modeling is accomplished by an inductive learning algorithm that is based on the concept of rough sets. The fuzzy process controller is constructed from the inverse fuzzy model. Therefore, it tries to cancel the dynamics of system in order to maintain the desired set-point. We demonstrate that the rough set based methodology can construct fuzzy models with good prediction capabilities using a minimal a priori knowledge about the system. Similar to other inverse model based controllers, the inverse model based fuzzy controllers behave like high pass filters that may amplify the noise and cause saturations in the actuators. Practical remedies to this problem are discussed. Two examples are given to illustrate the methodology.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, University of Akron, Akron, Ohio, 44325-3903, USA

    C. Batur

  2. Department of Mathematical Sciences, University of Akron, Akron, Ohio, 44325-4002, USA

    C.-C. Chan

  3. Neural Application Corp., Oakdale Research Park, 2600 Crosspark Road, Coralville, Iowa, 52241-3212, USA

    A. Srinivasan

Authors
  1. C. Batur
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  2. C.-C. Chan
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  3. A. Srinivasan
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece

    Spyros G. Tzafestas

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© 1997 Springer Science+Business Media Dordrecht

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Batur, C., Chan, CC., Srinivasan, A. (1997). Fuzzy Model Based Predictive Controller. In: Tzafestas, S.G. (eds) Methods and Applications of Intelligent Control. Microprocessor-Based and Intelligent Systems Engineering, vol 16. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-5498-7_6

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  • DOI: https://doi.org/10.1007/978-94-011-5498-7_6

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-6314-2

  • Online ISBN: 978-94-011-5498-7

  • eBook Packages: Springer Book Archive

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