A Universal Adaptive Neural Control Scheme for Nonlinear Uncertain System

Abstract:

The traditional BP algorithm is modified and a kind of novel model reference adaptive control (MRAC) scheme is proposed based on generalized BP (GBP) algorithm. The convergence of the control scheme is also analyzed according to Lyapunov theory. To test its effectiveness, the proposed model is used to control a nonlinear uncertain system. Simulation results indicate that the controller is effective in controlling a general class of nonlinear systems.

• Periodical: Applied Mechanics and Materials (Volumes 462-463)
• Pages: 553-557
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.462-463.553
• Online since: November 2013
• Authors: Huai Qing Ren, Yan Chun Liang, Xiao Hu Shi*
• Keywords: Adaptive Neural Control, Bp Learning Algorithm, Closed-Loop Control, Nonlinear System

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