Holographic neural network, which is a new algorithm of neural network, is applied to the control of a vehicle suspension. For the simplified suspension model, using the feedback gain obtained from the optimal control theory, the equation of motion is solved by Runge-Kutta method. The displacement, velocity, and control force obtained are adopted as training data for neural network. In the simulation the road displacement is assumed to be sinusoidal and its frequency is changed from 1.0Hz to 4.0Hz by 0.1Hz intervals. As the trained network is tested, the results for the road frequency not contained in the training data agree well with the results obtained from the optimal control theory.


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    Title :

    Control of vehicle suspension using neural network


    Contributors:

    Published in:

    Publication date :

    2004


    Size :

    9 Seiten, 3 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Control of vehicle suspension using neural network

    Kozukue, W. / Miyaji, H. / International Association for Vehicle System Dynamics | British Library Conference Proceedings | 2004


    Control of vehicle suspension using neural network

    Kozukue,W. / Miyaji,H. / Kanagawa Inst.of Technology,JP | Automotive engineering | 2004



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