Co-design of observer-based multiple weighting event-triggered and quadruple asynchronous control for fuzzy semi-Markov jump systems

IF 8.1 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yiteng Zhang , Linchuang Zhang , Wei Wang , Zhechen Zhu
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引用次数: 0

Abstract

This paper studies the co-design issue of observer-based dual multiple weighting event-triggered and quadruple asynchronous control for the Takagi-Sugeno fuzzy semi-Markov jump systems with actuator faults. Owing to the network-induced delay, external disturbance and other factors, the premise variables and modes information among the system, event generators, observer and controller cannot always match. In addition, there are often unmeasurable state variables and waste of limited network resources in practical systems. Therefore, an asynchronous observer-based controller and two multiple weighting asynchronous event-triggered schemes are developed simultaneously for the fuzzy semi-Markov jump systems by using hidden semi-Markov models. Based on the above quadruple asynchronous control framework, new sufficient conditions are developed to ensure that the related parameters of the designed observer, controller and event generators can be obtained. Eventually, the effectiveness of the proposed method is demonstrated by two simulation examples, with the second example ensuring the stable operation of the tunnel diode circuit system.
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来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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