Inverse Fuzzy Process Models for Robust Hybrid Control

  • M. Fischer
  • R. Isermann
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 16)


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.


Membership Function Fuzzy Model Inverse Model Radial Basis Function Network Disturbance Observer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • M. Fischer
    • 1
  • R. Isermann
    • 1
  1. 1.Institute of Automatic Control, Laboratory for Control Systems and Process AutomationDarmstadt University of TechnologyDarmstadtGermany

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