Inverse Fuzzy Model Based Predictive Control

  • R. Babuška
  • J. M. Sousa
  • H. B. Verbruggen
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 16)


Conventional fuzzy control is based on expert knowledge in the form of fuzzy if-then rules. Practice shows, however, that it is often not possible to collect sufficient information to design a well-performing fuzzy controller. Human control skills are generally difficult to verbalize, since the operator’s control strategy is often based on the simultaneous use of various control principles, combining feedforward, feedback, and predictive strategies in a complex, time-varying fashion. In such a case, the operator may not be able to explain why a particular control action is chosen. Moreover, the rules provided by different operators are often contradictory.


Fuzzy Model Prediction Horizon Internal Model Control Predictive Controller Supply Temperature 
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

  • R. Babuška
    • 1
  • J. M. Sousa
    • 1
  • H. B. Verbruggen
    • 1
  1. 1.Control Laboratory, Department of Electrical EngineeringDelft University of TechnologyDelftThe Netherlands

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