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

X.Z. Pan, J.J. Huang and S.M. Lee

Applied Mathematics and Computation, 2023, vol. 451, issue C

Abstract: 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 stabilization 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.

Keywords: Parameterized linear matrix inequalities (PLMIs); Affine matched premises; Sampled-data control; Convex relaxation technique; Fuzzy semi-Markov jump system (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:451:y:2023:i:c:s0096300323001959

DOI: 10.1016/j.amc.2023.128026

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