Output-feedback control design for Takagi-Sugeno fuzzy systems through Lyapunov functions depending polynomially on the states

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Yara Quilles-Marinho, Ricardo C.L.F. Oliveira, Pedro L.D. Peres
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引用次数: 0

Abstract

This paper proposes a new strategy based on linear matrix inequalities (LMIs) for the synthesis of state- and output-feedback controllers through parallel distributed compensation for continuous-time Takagi-Sugeno fuzzy systems. The main novelty of the proposed design technique is the use of homogeneous polynomial Lyapunov functions of degree larger than two on the states, generalizing the results based on quadratic functions. Parametrized in terms of a constant matrix, those homogeneous polynomial Lyapunov functions provide less conservative results in terms of stability and decay rate of trajectories when dealing with membership functions whose time-derivatives have unknown bounds. The synthesis procedure is formulated in terms of a locally convergent iterative algorithm, where a set of LMIs defined in an augmented parameter space is solved at each iteration. Numerical examples are used to compare the proposed method with quadratic stabilizability techniques available in the literature, illustrating the advantages of higher degree Lyapunov functions.
通过取决于多项式状态的 Lyapunov 函数设计高木-菅野模糊系统的输出反馈控制装置
本文提出了一种基于线性矩阵不等式(LMI)的新策略,用于通过并行分布式补偿合成连续时间高木-菅野模糊系统的状态和输出反馈控制器。所提设计技术的主要新颖之处在于使用了阶数大于 2 的同次多项式 Lyapunov 函数,从而推广了基于二次函数的结果。这些同次多项式 Lyapunov 函数以常数矩阵为参数,在处理时间导数具有未知边界的成员函数时,在轨迹的稳定性和衰减率方面提供了不太保守的结果。合成过程采用局部收敛迭代算法,每次迭代都会求解一组在增强参数空间中定义的 LMI。利用数值示例比较了所提出的方法和文献中的二次稳定技术,说明了高阶 Lyapunov 函数的优势。
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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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