A direct adaptive fuzzy approach is presented for parameter identification and control of unknown nonlinear systems. To prove the performance of the proposed method an AUV (Autonomous Underwater Vehicle) is modeled using an ANFIS (Adaptive Neuro-Fuzzy Inference System). To guaranty high accuracy the model is adapted online using system input and output data. From the model the current process parameters are identified and utilized for controller design. Here, single step ahead direct adaptive control and multi steps ahead direct control schemes are considered.


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    Title :

    Neuro-fuzzy adaptive control and modeling a thruster of autonomous underwater vehicles


    Additional title:

    Neuro-Fuzzy-Adaptivregelung und Modellbildung eines Schuberzeugers für ein autonomes Unterwasserfahrzeug


    Contributors:
    Palis, F. (author) / Tsepkovskiy, Y. (author) / Filaretov, V. (author) / Ukhimets, D. (author)


    Publication date :

    2006


    Size :

    7 Seiten, 10 Bilder, 1 Tabelle, 14 Quellen


    Type of media :

    Conference paper


    Type of material :

    Storage medium


    Language :

    English