Focusing on the nonlinear and uncertain characteristics of suspension system,a 2-DOF vehicle is regarded as the control object, sliding mode theory was used to design a sliding mode controller for the 2 DOFs vehicle semi-active suspension system,then RBF neural network was employed to optimize the sliding mode controller.The control effects of three key performance parameters of suspension, the acceleration of car body, the dynamic travel of suspension and the dynamic deflection of tire are studied under random excitation conditions.The results indicate that in comparison with the passive suspension,sliding mode semi-active control based on RBF neural network can improve suspension performance effectively.


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    Title :

    The Simulation of Semi-Active Suspension System Based on RBF Neural Network Sliding Mode Control


    Contributors:

    Published in:

    Applied Mechanics and Materials ; 229-231 ; 1763-1767


    Publication date :

    2012-11-29


    Size :

    5 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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