This paper presents a design methodology for an on-line self-tuning adaptive control (OLSTAC) of a single flexible link manipulator (FLM) using backpropagation neural networks (BPNN). The particular problem discussed is the on-line system identification of a FLM using BPNN and the OLSTAC of a FLM using a separate neural network as a controller. A finite-element model of a FLM is obtained using ANSYS. The pseudo-link concepts developed in (2) are used to determine on-line angular displacement of the end effector of the FLM. The illustrative simulation results are promising and show that the OLSTAC technique can be applied to flexible structures such as a FEM resulting reduced error and increased robustness.<>


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    Title :

    Neural network based adaptive control of a flexible link manipulator


    Contributors:
    Mahmood, N. (author) / Walcott, B.L. (author)


    Publication date :

    1993-01-01


    Size :

    540259 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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