Command filtered‐based fixed‐time fault‐tolerant tracking control for nonlinear systems

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Robust and Nonlinear Control Pub Date : 2024-09-02 DOI:10.1002/rnc.7619
Yingsen Li, Ming Chen, Kaixiang Peng, Huanqing Wang
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Abstract

As for a class of strict‐feedback nonlinear systems with simultaneous sensor and actuator faults, the article focuses on the problem of fixed‐time fault‐tolerant control. Both fixed‐time command filters and a compensation mechanism are utilized to cope with these issues of differential explosion and filter errors. Meanwhile, through the fusion of fixed‐time control, fuzzy logic systems, adaptive control and the backstepping technology, a ‐step design scheme is presented. Our proposed controller ensures the fixed‐time convergence of all the signals in the system even with sensor/actuator faults, and allows the designers to acquire the upper limit value of the fixed convergence time only by tuning the design parameters. And this scheme takes into account rapidity, adaptability and fault tolerance of the system simultaneously. Based on the numerical simulation analysis, it is shown that the better tracking performance can be achieved. So it is concluded that our strategy is effective.
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基于指令滤波的非线性系统固定时间容错跟踪控制
对于一类同时存在传感器和执行器故障的严格反馈非线性系统,文章重点讨论了固定时间容错控制问题。文章利用固定时间指令滤波器和补偿机制来应对差分爆炸和滤波器误差问题。同时,通过将固定时间控制、模糊逻辑系统、自适应控制和反步进技术相结合,提出了一种阶跃设计方案。即使在传感器/执行器出现故障的情况下,我们提出的控制器也能确保系统中所有信号的固定时间收敛,而且设计人员只需调整设计参数就能获得固定收敛时间的上限值。该方案同时兼顾了系统的快速性、适应性和容错性。基于数值仿真分析,可以获得更好的跟踪性能。因此可以得出结论,我们的策略是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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