Feiyue Shen , Haoyi Zhang , Wenhai Qi , Ju H. Park , Jun Cheng , Kaibo Shi
{"title":"Nonfragile anti-transitional-asynchrony fault tolerant control for IT2 fuzzy semi-Markov jump systems with actuator failures","authors":"Feiyue Shen , Haoyi Zhang , Wenhai Qi , Ju H. Park , Jun Cheng , Kaibo Shi","doi":"10.1016/j.fss.2024.109176","DOIUrl":null,"url":null,"abstract":"<div><div>This paper studies the nonfragile anti-transitional-asynchrony fault tolerant control for discrete interval type-2 fuzzy semi-Markov jump systems with bounded dwell time. In contrast to the traditional Takagi-Sugeno (T-S) fuzzy model, this paper utilises the interval 2-type fuzzy model to represent the nonlinear discrete semi-Markov jump systems. The main novelty is to design an anti-transitional-asynchrony fault-tolerant control mechanism with controller gain fluctuations under the framework of IT2 fuzzy, fault-tolerant control, and transitional asynchrony, which reduces the conservatism to a certain extent. The transitional asynchrony is adopted, i.e., the controller switching lags behind the plant switching, and this lag is associated with the transition between the current mode and the next mode. By virtue of semi-Markov kernel method, the mean-square stability of the underlying system is achieved, overcoming the difficulties caused by the transitional asynchrony. In addition, taking into account that the actuator may encounter random faults during system operation, this paper applies a fault tolerant method in the design of nonfragile anti-transitional-asynchrony control to improve the fault tolerance of the system. Finally, a tunnel circuit model verifies the effectiveness of the designed control method.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"499 ","pages":"Article 109176"},"PeriodicalIF":3.2000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fuzzy Sets and Systems","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165011424003221","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper studies the nonfragile anti-transitional-asynchrony fault tolerant control for discrete interval type-2 fuzzy semi-Markov jump systems with bounded dwell time. In contrast to the traditional Takagi-Sugeno (T-S) fuzzy model, this paper utilises the interval 2-type fuzzy model to represent the nonlinear discrete semi-Markov jump systems. The main novelty is to design an anti-transitional-asynchrony fault-tolerant control mechanism with controller gain fluctuations under the framework of IT2 fuzzy, fault-tolerant control, and transitional asynchrony, which reduces the conservatism to a certain extent. The transitional asynchrony is adopted, i.e., the controller switching lags behind the plant switching, and this lag is associated with the transition between the current mode and the next mode. By virtue of semi-Markov kernel method, the mean-square stability of the underlying system is achieved, overcoming the difficulties caused by the transitional asynchrony. In addition, taking into account that the actuator may encounter random faults during system operation, this paper applies a fault tolerant method in the design of nonfragile anti-transitional-asynchrony control to improve the fault tolerance of the system. Finally, a tunnel circuit model verifies the effectiveness of the designed control method.
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.