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Inverse Fuzzy Process Models for Robust Hybrid Control

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Advances in Fuzzy Control

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 16))

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Abstract

Fuzzy controllers are on their way of becoming a standard tool in industrial automation. [13] gives an overview of possible control concepts involving fuzzy components. It turns out that the application of fuzzy control is particularly effective at the higher levels of automation systems. For this purpose, direct fuzzy controllers are usually designed manually. Experts’ knowledge is used to determine the membership functions and the rule base (Fig. 1). This approach allows a fast controller prototyping, but the optimization of the controller usually requires a tedious tuning procedure due to the great number of free parameters and incomplete heuristic knowledge.

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Author information

Authors and Affiliations

  1. Institute of Automatic Control, Laboratory for Control Systems and Process Automation, Darmstadt University of Technology, Landgraf-Georg-Str. 4, D-64283, Darmstadt, Germany

    M. Fischer & R. Isermann

Authors
  1. M. Fischer
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  2. R. Isermann
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Linköping, S-58183, Linköping, Sweden

    Dimiter Driankov

  2. Corporate Technology Information and Communications, Dept. ZT IK4, Siemens AG, D-81730, Munich, Germany

    Rainer Palm

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© 1998 Springer-Verlag Berlin Heidelberg

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Fischer, M., Isermann, R. (1998). Inverse Fuzzy Process Models for Robust Hybrid Control. In: Driankov, D., Palm, R. (eds) Advances in Fuzzy Control. Studies in Fuzziness and Soft Computing, vol 16. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1886-4_5

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  • DOI: https://doi.org/10.1007/978-3-7908-1886-4_5

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-662-11053-9

  • Online ISBN: 978-3-7908-1886-4

  • eBook Packages: Springer Book Archive

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