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

Hua Zhu

doi:10.4028/www.scientific.net/AMM.229-231.1763

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 229-231The Simulation of Semi-Active Suspension System...

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

Abstract:

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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Periodical:

Applied Mechanics and Materials (Volumes 229-231)

Pages:

1763-1767

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.229-231.1763

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Online since:

November 2012

Authors:

Hua Zhu

Keywords:

RBF Neural Network, Semi-Active Suspension, Simulation

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