Synthetic static output feedback control for fuzzy systems under fault derivative transformation based fault accommodation

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Hong-Jun Wang , Sheng-Juan Huang
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引用次数: 0

Abstract

This work examines the problem of synthetic static output feedback control embedded fault derivative transformation based fault accommodation for Takagi-Sugeno (T-S) fuzzy systems beset by actuator faults. To implement the fault accommodation more effectively, a fault derivative transformation technique is introduced to design a synthetic observer structure with more relaxed parameters. In the process of stability analysis, a linear transformation matrix (LTM) factor based Lyapunov function is employed to eliminate the coupling terms in the derived matrix inequalities, so as to obtain the linear matrix inequality (LMI) based stability conditions. Furthermore, an improved inequality scaling method is proposed to reduce the conservatism of the LMI-based stability conditions. Two numerical examples represented by T-S fuzzy models test the designed synthetic control strategy.
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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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