Neuro-Identifier-Based Tracking Control of Uncertain Chaotic System

Authors:
Wen Tan;Fuchun Sun;Yaonan Wang;Shaowu Zhou
Affiliations:
School of electrical and information engineering, Hunan University of Science and technology, Xiangtan, P.R. China 411201;Dept.of Computer Science and Technology, Tsinghua University, Beijing, P.R. China 100084;College of electrical and information engineering, Hunan University, Changsha, P.R. China 410082;School of electrical and information engineering, Hunan University of Science and technology, Xiangtan, P.R. China 411201
Venue:
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
Year:
2008

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Abstract

A novel neuro-identifier-based tracking control of uncertain nonlinear chaotic system is presented. The algorithm is divided into two contributions. First, a dynamic neural networks is used to identify the unknown chaos, then a dynamic adaptive state feedback controller based on neuro-identifier is derived to direct the unknown chaotic system into desired reference model trajectories. Moreover, the identification error and trajectory error is theoretically verified to be bounded and converge to zero Computer simulations are shown to demonstrate the effectiveness of this proposed methodology.