Adaptive neural network control for switched system with unknown nonlinear part by using backstepping approach: SISO case

Authors:
Fei Long;Shumin Fei;Zhumu Fu;Shiyou Zheng
Affiliations:
Department of Automatic Control, Southeast University, Nanjing, P.R. China;Department of Automatic Control, Southeast University, Nanjing, P.R. China;Department of Automatic Control, Southeast University, Nanjing, P.R. China;Department of Automatic Control, Southeast University, Nanjing, P.R. China
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

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Abstract

In this paper, we address, in a backstepping way, stabilization problem for a class of switched nonlinear systems whose subsystem with trigonal structure by using neural network. An adaptive neural network switching control design is given. Backsteppping, domination and adaptive bounding design technique are combined to construct adaptive neural network stabilizer and switching law. Based on common Lyapunov function approach, the stabilization of the resulting closed-loop systems is proved.