Adaptive Neural Control with Prescribed Performance for Strict-Feedback Systems with Input Saturation

Jingliang Sun, Chunsheng Liu*

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper presents a novel adaptive control scheme that is able to achieve given tracking performance for a class of uncertain nonlinear systems in strict-feedback form with input saturation. The neural networks (NNs) are utilized to estimate the unknown nonlinearities, and an auxiliary system is designed to compensate the effect of input saturation. Different from the existing results, a novel barrier Lyapunov function is firstly introduced into the backstepping design step to deal with the tracking error performance. Therefore, it is a unified design approach for systems with or without constraint requirements. Finally, by utilizing the Lyapunov method, the boundedness of the closed-loop signals is guaranteed, and the tracking error is constrained within prescribed performance bound. The simulation results illustrate the effectiveness of the proposed control approach.

源语言英语
主期刊名2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781538611715
DOI
出版状态已出版 - 8月 2018
已对外发布
活动2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018 - Xiamen, 中国
期限: 10 8月 201812 8月 2018

出版系列

姓名2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018

会议

会议2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018
国家/地区中国
Xiamen
时期10/08/1812/08/18

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