An augmented system approach for LMI-based control design of constrained Takagi-Sugeno fuzzy systems. (May 2017)

• Record Type: Journal Article
• Authors: Nguyen, Anh-Tu; Márquez, Raymundo; Dequidt, Antoine
• Is Part Of: Engineering applications of artificial intelligence. Volume 61(2017:Jan.)
• Page Start: 96
• Page End: 102
• Publication Date: 2017-05
• Subjects: Takagi-Sugeno fuzzy systems -- Constrained control -- System augmentation approach -- L2-gain performance -- Linear matrix inequality (LMI); Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2016.11.011
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: In this paper, we address the control design of a class of constrained Takagi-Sugeno fuzzy systems. These systems are subject to both control input and state constraints. Sufficient design conditions are derived via a judicious use of an equivalent augmentation form of the closed-loop system together with a new parameter-dependent Lyapunov function. The control input nonlinearity is dealt with via a generalized sector condition. These instrumental control tools allow reducing significantly the conservatism of the results while keeping a simple control structure with a low level of numerical complexity. In particular, it has been shown that in many cases the new method can provide better results (in terms of conservatism reduction) than some recent works developed in non-quadratic Lyapunov framework. Several numerical examples are given to illustrate the effectiveness of the proposed method.