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Adaptive backstepping control for a class of nonlinear systems using neural network approximations

机译:基于神经网络逼近的一类非线性系统的自适应反步控制

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摘要

In this paper, an adaptive neural network (NN) backstepping technique is developed for tracking control of a class of nonlinear systems. NNs are used to compensate for the unknown nonlinear functions in the system. A systematic backstepping approach is established to synthesize the adaptive NN control scheme that ensures the boundedness of all the signals in the closed-loop system, and yields a small tracking error. The issue of transient performance is also addressed under an analytical framework. The effectiveness of the proposed scheme is demonstrated by computer simulations. Copyright (C) 2004 John Wiley Sons, Ltd.
机译:本文提出了一种自适应神经网络(NN)反推技术,用于一类非线性系统的跟踪控制。 NN用于补偿系统中未知的非线性函数。建立了系统的反推方法来合成自适应神经网络控制方案,该方案可确保闭环系统中所有信号的有界性,并产生较小的跟踪误差。在分析框架下也解决了瞬态性能问题。计算机仿真证明了该方案的有效性。版权所有(C)2004 John Wiley Sons,Ltd.

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