Robust adaptive control for a class of switched nonlinear systems in pure-feedback form

Bai-Cheng Zhu, Tianping Zhang
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引用次数: 5

Abstract

An adaptive neural network control scheme is proposed for a class of nonlinear switched systems in pure-feedback form. The design is based on the dynamic surface technique, the approximation capability of neural networks and the dwell-time approach. The design makes the approach of dynamic surface control being extended to the switched nonlinear system, and relaxes the extent of application of the approach of dynamic surface control. Compared with existing literatures, the proposed approach relaxes the requirements of the system. And the explosion of complexity in traditional backstepping design caused by repeated differentiations of virtual control is avoided. By theoretical analysis, the closed-loop control system is shown to be semi-globally uniformly ultimately bounded. Finally, simulation results are presented to illustrate the effectiveness of the proposed approach.
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一类纯反馈切换非线性系统的鲁棒自适应控制
针对一类纯反馈非线性切换系统,提出了一种自适应神经网络控制方案。该设计基于动态曲面技术、神经网络的逼近能力和驻留时间法。该设计使动态面控制方法推广到切换非线性系统,放宽了动态面控制方法的应用范围。与现有文献相比,该方法放宽了对系统的要求。避免了传统退步设计中由于虚拟控制的重复微分而导致的复杂度爆炸。通过理论分析,证明了闭环控制系统是半全局一致最终有界的。最后给出了仿真结果,验证了所提方法的有效性。
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