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Neural networks direct adaptive control for a class of MIMO uncertain nonlinear systems

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4 Author(s)
Tingliang Hu ; Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China ; Jihong Zhu ; Chunhua Hu ; Zengqi Sun

This paper presents a direct adaptive control scheme based on multi-layer neural networks for a class of multi-input multi-output (MIMO) nonlinear systems with unknown nonlinearity. The on-line updating rules of the neural networks parameters are obtained by Lyapunov stability theory. All signals in the closed-loop system are bounded and the output tracking error converges to a small neighborhood of zero. In this sense the closed-loop system is stable. The effectiveness of the control scheme is verified by a simulation of two link manipulator.

Published in:

Soft Computing in Industrial Applications, 2005. SMCia/05. Proceedings of the 2005 IEEE Mid-Summer Workshop on

Date of Conference:

28-30 June 2005