Tracking Control System Design Based on Adaptive Neural Network

Abstract:

The implicit function theorem and the mean value theorem non-affine function of the system into an affine form, and then RBF neural network approximation virtual control and actual control signals desired. Finally Lyapunov functional theory and backstepping method are used to design a self-adapt tracking control scheme. The proposed control scheme can guaranteed to achieve better tracking performance, thus avoiding the problems caused by the high-gain control affine term sector caused by design problems and overcome loop controller. In order to solve practical engineering control problems provides a theoretical basis and can learn from the ideas, and finally through numerical examples to demonstrate the effectiveness of the proposed method.

• Periodical: Applied Mechanics and Materials (Volumes 536-537)
• Pages: 1236-1239
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.536-537.1236
• Online since: April 2014
• Authors: Liang Cheng*
• Keywords: Neural Network (NN), System Design, Tracking Systems, Virtual Control

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