This paper discusses the optimisation of a fuzzy-neural controller based on the paradigm of genetic search. The controller under consideration is a hybrid one which can be interpretated as a Takagi/Sugeno model of fuzzy inference or a basis function network. The discretisation of the search space must be addressed, encoding methods for the fuzzy rulebase and the construction of a fitness evaluation procedure. The developed techniques are applied to the problem of lateral control of an autonomous vehicle based on a linearized time varying model of the vehicle s response to steering inputs. The performance of the control system is measured by a complex cost function combining both passenger comfort and security aspects which is minimised by changing the parameters and structure of a fuzzy-neural contoller.


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    Title :

    Genetic-based optimisation of a fuzzy-neural vehicle controller


    Additional title:

    Optimierung einer neuronalen Fuzzy-KFZ-Steuereinrichtung auf der Basis genetischer Algorithmen


    Contributors:
    Haas, R. (author) / Hunt, K.J. (author)


    Publication date :

    1994


    Size :

    13 Seiten, 7 Bilder, 20 Quellen


    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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