Hierarchical admissibility criteria for T-S fuzzy singular systems with time-varying delay

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS Fuzzy Sets and Systems Pub Date : 2024-07-02 DOI:10.1016/j.fss.2024.109065
Yun Chen , Gang Chen
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Abstract

This paper studies the admissibility analysis for Takagi-Sugeno (T-S) fuzzy singular systems with a time-varying delay. A novel Lyapunov-Krasovskii functional (LKF) approach, named a delay-interval-based piecewise Lyapunov functional, is first introduced. This LKF enables the use of distinct delay-dependent matrices for each partitioned delay subinterval, thereby providing additional information on the delay and its derivative. Secondly, a zero equation approach with delay-variation-dependent free matrices is presented to avoid the appearance of the delay-dependent quadratic function after the LKF's derivative. Subsequently, a cluster of admissibility criteria for the considered systems is derived by incorporating the Bessel-Legendre integral inequality. These criteria exhibit hierarchy, which means that the larger the number of delay-interval partitions, the less conservatism. Finally, the efficacy of the proposed methods is validated through numerical examples.

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具有时变延迟的 T-S 模糊奇异系统的分层可接受性标准
本文研究了具有时变延迟的高木-菅野(T-S)模糊奇异系统的可接受性分析。首先介绍了一种新颖的 Lyapunov-Krasovskii 函数(LKF)方法,即基于延迟时间的片断 Lyapunov 函数。这种 LKF 可以为每个分区延迟子区间使用不同的延迟相关矩阵,从而提供有关延迟及其导数的额外信息。其次,介绍了一种零方程方法,该方法采用了与延迟变化相关的自由矩阵,以避免在 LKF 的导数之后出现与延迟相关的二次函数。随后,通过结合贝塞尔-勒根德积分不等式,得出了所考虑系统的一组可接受性标准。这些标准呈现出层次性,即延迟间隔分区的数量越多,保守性就越小。最后,通过数值示例验证了所提方法的有效性。
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来源期刊
Fuzzy Sets and Systems
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.
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