A novel convex relaxation technique on affine transformed sampled-data control issue for fuzzy semi-Markov jump systems

Citations

WEB OF SCIENCE

6
Citations

SCOPUS

7

초록

This article investigates affine transformed sampled-data control problems for fuzzy semi-Markov jump systems (FSMJSs). First of all, in the novel fuzzy sampled-data control, an affine transformed membership function is introduced, which contributes to constructing the synchronous time scale grades of membership without any constraint condition. Then, by utilizing a mode-dependent Lyapunov function with the looped functions, a sufficient condition concerning the asymptotical stability of the closed-loop FSMJSs is established in the form of linear matrix inequality (LMI). Meanwhile, to solve parameterized LMI (PLMI), a novel convex relaxation technique is proposed, based on which less conservatism stabi-lization criteria of FSMJSs, and a maximum sampling interval with respect to sampled-data control are further derived. Finally, two examples are carried out to manifest numerically the validity of the raised method.(c) 2023 Elsevier Inc. All rights reserved.

키워드

Parameterized linear matrix inequalities; (PLMIs); Affine matched premises; Sampled-data control; Convex relaxation technique; Fuzzy semi-Markov jump system; STABILIZATION; STABILITY; MATRIX; MODEL
제목
A novel convex relaxation technique on affine transformed sampled-data control issue for fuzzy semi-Markov jump systems
저자
Pan, X. Z.; Huang, J. J.; Lee, S. M.
DOI
10.1016/j.amc.2023.128026
발행일
2023-08-15
유형
Article
저널명
Applied Mathematics and Computation
권
451