Adaptive Dynamic Surface Control for Car Driving Simulator based on Artificial Neural Network

This paper presents an adaptive controller for a four degrees of freedom car driving simulator. The actual model of the simulator is often deficient in the system's parameters or has the nonlinear uncertainties. Therefore an adaptive dynamic surface control based on radial basis function neural network is proposed to approximate the uncertain elements and ensure the stability of the system at the same time. The stability of the system is proved based on Lyapunov theorem. Simulation results verify the effectiveness and accuracy of the proposed algorithm and the comparison between using neural network and not using this element indicates the superiority of the proposed controller.