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An Online SMC-Based Adaptive Wavelet-Neural Controller for Uncertain Nonlinear Systems with only Output Measurement

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Abstract:

This paper addresses the SMC-based adaptive wavelet-neural tracking control problem for a class of uncertain nonlinear systems. The adaptive wavelet-neural controller is designed under constrain that not all atate variables are available for measurement. A state observer is used to estimate unmeasured states of the systems. The global asymptotic stability of the closed-loop system is guaranteed according to the Lyapunov stability criterion. The simulation presented in the inverted pendulum system control indicates that the proposed approach is capable of achieving a good trajectory following performance without the knowledge of plant parameters.

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Periodical:

Advanced Materials Research (Volume 413)

Pages:

551-556

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.413.551

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Online since:

December 2011

Authors:

Chun Sheng Chen

Keywords:

Nonlinear System, Observer, Sliding Mode Control (SMC), Wavelet Neural Network (WNN)

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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