Adaptive memory-event-triggered-based double asynchronous fuzzy control for nonlinear semi-Markov jump systems

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

Fuzzy Sets and Systems Pub Date : 2025-04-14 DOI:10.1016/j.fss.2025.109405

Yanmin Wu , Wei Qian

{"title":"Adaptive memory-event-triggered-based double asynchronous fuzzy control for nonlinear semi-Markov jump systems","authors":"Yanmin Wu , Wei Qian","doi":"10.1016/j.fss.2025.109405","DOIUrl":null,"url":null,"abstract":"<div><div>This article is concerned with the double asynchronous fuzzy control scheme for networked nonlinear semi-Markov jump systems with uncertainties. With the help of interval type-2 Takagi-Sugeno fuzzy technique, nonlinear semi-Markov jump systems are described. To reduce the transmission of dispensable packets, an adaptive memory-event-triggered mechanism, which constructs a new adaptive update rule taking historical data, is proposed for further optimizing communication efficiency. Considering the premise variables asynchronous phenomenon and the model asynchronous problem, the asynchronous premise reconstruction strategy as well as the hidden semi-Markov model are employed simultaneously, for effectively copying with the double asynchronous issue. Then, a double asynchronous memory controller is devised in light of adaptive event-triggered mechanism to ensure that the closed-loop systems can obtain better system control performance by the means of utilizing less data. Eventually, some simulation results are presented for the sake of demonstrating the practicability and superiority of the investigated control technique.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"514 ","pages":"Article 109405"},"PeriodicalIF":3.2000,"publicationDate":"2025-04-14","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/S0165011425001447","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 article is concerned with the double asynchronous fuzzy control scheme for networked nonlinear semi-Markov jump systems with uncertainties. With the help of interval type-2 Takagi-Sugeno fuzzy technique, nonlinear semi-Markov jump systems are described. To reduce the transmission of dispensable packets, an adaptive memory-event-triggered mechanism, which constructs a new adaptive update rule taking historical data, is proposed for further optimizing communication efficiency. Considering the premise variables asynchronous phenomenon and the model asynchronous problem, the asynchronous premise reconstruction strategy as well as the hidden semi-Markov model are employed simultaneously, for effectively copying with the double asynchronous issue. Then, a double asynchronous memory controller is devised in light of adaptive event-triggered mechanism to ensure that the closed-loop systems can obtain better system control performance by the means of utilizing less data. Eventually, some simulation results are presented for the sake of demonstrating the practicability and superiority of the investigated control technique.

查看原文本刊更多论文

非线性半马尔可夫跳变系统的自适应记忆事件触发双异步模糊控制

研究了具有不确定性的网络非线性半马尔可夫跳变系统的双异步模糊控制方案。利用区间2型Takagi-Sugeno模糊技术，描述了非线性半马尔可夫跳变系统。为了减少不必要数据包的传输，提出了一种自适应内存事件触发机制，该机制构造了一种新的基于历史数据的自适应更新规则，进一步优化通信效率。考虑到前提变量异步现象和模型异步问题，同时采用异步前提重构策略和隐半马尔可夫模型，对双异步问题进行有效复制。然后，根据自适应事件触发机制设计了双异步存储器控制器，以保证闭环系统以较少的数据量获得较好的系统控制性能。最后给出了一些仿真结果，以证明所研究控制技术的实用性和优越性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

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.