Research on a direct adaptive neural network control method of nonlinear systems

Authors:
Weijin Jiang;Yusheng Xu;Yuhui Xu
Affiliations:
Department of Computer, Zhuzhou Institute of Technology, Zhuzhou, P.R.China;College of Mechanical Engineering and Applied Electronics, Beijing University of Technology, Beijing, P.R.China;Department of Computer, Zhuzhou Institute of Technology, Zhuzhou, P.R.China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Year:
2005

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Abstract

The problem of direct adaptive neural control for a class of nonlinear systems with an unknown gain sign and nonlinear uncertainty is discussed in this paper. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks (MNNs), and using Nussbaum-type function, a novel design scheme of direct adaptive neural control is proposed. By adopting the adaptive compensation term of the upper bound function of the sum of residual and approximation error, the closed-loop control system is shown to be globally stable, with tracking error converging to zero. Simulation results show the effectiveness of the proposed approach.