非线性奇摄动跳跃系统的区间2型模糊H∞滤波:半马尔可夫核方法

IF 2.7 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS Fuzzy Sets and Systems Pub Date : 2025-04-01 Epub Date: 2025-01-08 DOI:10.1016/j.fss.2025.109264
Hao Shen , Guanqi Wang , Jianwei Xia , Ju H. Park , Xiang-Peng Xie
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引用次数: 0

摘要

研究了具有半马尔可夫过程的非线性奇摄动跳跃系统的H∞滤波问题。采用区间2型模糊模型处理系统固有的不确定性和非线性。该方法利用半马尔可夫核方法和非并行分布补偿技术,设计了一种与系统模式相关但不受奇异扰动参数影响的区间2型模糊滤波器。为了保证滤波误差系统在满足指定的H∞性能的情况下均方指数稳定,导出了包含隶属函数信息的准则。引入带有两个可调标量的松弛矩阵便于获得区间2型模糊滤波增益。通过两个算例,包括一个电路模型,验证了所提方法的合理性。
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Interval type-2 fuzzy H∞ filtering for nonlinear singularly perturbed jumping systems: A semi-Markov kernel method
This paper addresses the H filtering issue for nonlinear singularly perturbed jump systems with semi-Markov process. The interval type-2 fuzzy model is employed to handle the uncertain features and nonlinearity inherent in the considered systems. Designing an interval type-2 fuzzy filter, it is related to the system mode but remains independent of the singular perturbation parameter, this approach utilizes the semi-Markov kernel method and non-parallel distributed compensation technique. Some criteria with incorporating the message of membership functions are derived to ensure that the filtering error system is mean-square exponentially stable while meeting specified H performance. Introduction of slack matrices with two adjustable scalars facilitates obtaining the interval type-2 fuzzy filter gains. The rationality of the proposed approach is demonstrated through the utilization of two examples, including a circuit model.
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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.
期刊最新文献
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