具有非对称死区的不确定开关非线性系统的自适应模糊固定时间控制

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

Fuzzy Sets and Systems Pub Date : 2024-09-27 DOI:10.1016/j.fss.2024.109119

Shuo Liu , Huaguang Zhang , Hongbo Pang

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引用次数: 0

摘要

本文探讨了具有非对称死区的不确定开关非线性系统的模糊自适应固定时间跟踪控制问题，即使子系统的跟踪控制问题无法求解。本文提出了一种使用 MLF（多重 Lyapunov 函数）方法的开关非线性系统定时稳定性准则。然后，将其应用于不确定严格反馈开关非线性系统的固定时间跟踪控制。给出了模糊自适应反馈控制器和与状态相关的开关律的设计方法，以实现闭环系统所有信号的有界性和固定时间输出跟踪控制。非对称死区模型用于通过较少的参数估计自适应因子，这与不确定开关非线性系统的固定时间跟踪控制有关。通过两个实例验证了所提设计方法的有效性。

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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Adaptive fuzzy fixed-time control for uncertain switched nonlinear systems with non-symmetrical dead-zone

This paper addresses fuzzy adaptive fixed-time tracking control problem for uncertain switched nonlinear systems with non-symmetrical dead-zone, even if the tracking control problem for subsystems is not solvable. A fixed-time stability criterion for switched nonlinear systems using MLF(multiple Lyapunov functions) method is presented. Then, it is applied to fixed-time tracking control of uncertain strict-feedback switched nonlinear systems. The design methods of fuzzy adaptive feedback controllers and a state-dependent switching law are given to achieve the boundedness of all the signals of the resulting closed-loop system and the fixed-time output tracking control. Nonsymmetrical dead-zone model is used to estimate an adaptive factor through less parameters, which related to fixed-time tracking control for the uncertain switched nonlinear systems. Two examples are given to verify the effectiveness of the proposed design method.

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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.