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RBF neural network multi-step predictive control for nonlinear systems

FAN Zhao-feng;MA Xiao-ping;SHAO Xiao-gen;School of Information and Electrical Engineering,China University of Mining and Technology;College of Information and Electrical Engineering,Xuzhou Institute of Technology;  
Aim at solving the strong nonlinear control problem,a multi-step predictive control method is proposed,which uses a RBF neural network as a model.A multi-step predictive model is constructed,a Jacobian matrix computing method for predictive error about control sequence is given,a receding horizon optimization policy is designed by using L-M algorithm,feedback correction is achieved by modifying reference input according the error,and the stability of the system is proved.Simulation results of the control method validate desirable performances.
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