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RBF-based discrete sliding mode control for robust tracking of uncertain time-delay systems with input nonlinearity

机译:基于RBF的离散滑模控制,用于具有输入非线性的不确定时滞系统的鲁棒跟踪

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摘要

In this article, a control scheme combining radial basis function neural network and discrete sliding mode control method is proposed for robust tracking and model following of uncertain time-delay systems with input nonlinearity. The proposed robust tracking controller guarantees the stability of overall closed-loop system and achieves zero-tracking error in the presence of input nonlinearity, time-delays, time-varying parameter uncertainties, and external disturbances. The salient features of the proposed controller include no requirement of a priori knowledge of the upper bound of uncertainties and the elimination of chattering phenomenon and reaching phase. Simulation results are presented to demonstrate the effectiveness of the proposed scheme. (c) 2015 Wiley Periodicals, Inc. Complexity 21: 194-201, 2016
机译:本文提出了一种结合径向基函数神经网络和离散滑模控制方法的控制方案,用于具有输入非线性的不确定时滞系统的鲁棒跟踪和模型跟随。所提出的鲁棒跟踪控制器保证了整个闭环系统的稳定性,并在存在输入非线性,时滞,时变参数不确定性和外部干扰的情况下实现了零跟踪误差。所提出的控制器的显着特征包括不需要先验知识的不确定性上限以及消除颤振现象和到达阶段。仿真结果表明了该方案的有效性。 (c)2015 Wiley Periodicals,Inc.复杂性21:194-201,2016

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