Dynamic event-triggered fault-tolerant control for nonaffine systems with asymmetric error constraint

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems Pub Date : 2024-11-08 DOI:10.1016/j.fss.2024.109180

Yang Wu, Lianjun Hu, Qi Chen, Yong Zhang, Libing Wu

引用次数: 0

Abstract

This paper focuses on the problem of dynamic event-triggered fault-tolerant control (FTC) for nonaffine systems with unmeasurable state and asymmetric error constrain. At first, an adaptive failure compensation observer is designed to calculate unpredictable state of the nonaffine systems. Then, a dynamic event triggering strategy (DETS) is constructed to adjust the control signal and make it more flexible in transmission. Next, a new error-dependent conversion function (EDCF) is designed to confine tracing error, which can ensure that the designed Lyapunov function is always positive definite, and extend the symmetric constraint boundary to the asymmetric constraint boundary. The tracking performance and stability of closed-loop systems are proven through Lyapunov stability analysis. Finally, the availability of this method is verified by simulation experiments.

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具有非对称误差约束的非石蜡系统的动态事件触发容错控制

本文重点研究了状态不可测、误差约束不对称的非线性系统的动态事件触发容错控制（FTC）问题。首先，设计了一个自适应故障补偿观测器来计算非石蜡系统的不可测状态。然后，构建了一种动态事件触发策略（DETS）来调整控制信号，使其在传输过程中更加灵活。接着，设计了一种新的误差相关转换函数（EDCF）来限制跟踪误差，从而确保所设计的 Lyapunov 函数始终为正定值，并将对称约束边界扩展到非对称约束边界。通过 Lyapunov 稳定性分析，证明了闭环系统的跟踪性能和稳定性。最后，通过仿真实验验证了该方法的可用性。

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

Fuzzy Sets and Systems 数学-计算机：理论方法

CiteScore

6.50

自引率

17.90%

发文量

321

审稿时长

6.1 months

期刊介绍： Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.