TY - JOUR
T1 - A novel convex relaxation technique on affine transformed sampled-data control issue for fuzzy semi-Markov jump systems
AU - Pan, X. Z.
AU - Huang, J. J.
AU - Lee, S. M.
N1 - Publisher Copyright:
© 2023 Elsevier Inc.
PY - 2023/8/15
Y1 - 2023/8/15
N2 - 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.
AB - 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.
KW - Affine matched premises
KW - Convex relaxation technique
KW - Fuzzy semi-Markov jump system
KW - Parameterized linear matrix inequalities (PLMIs)
KW - Sampled-data control
UR - https://www.scopus.com/pages/publications/85152590536
U2 - 10.1016/j.amc.2023.128026
DO - 10.1016/j.amc.2023.128026
M3 - Article
AN - SCOPUS:85152590536
SN - 0096-3003
VL - 451
JO - Applied Mathematics and Computation
JF - Applied Mathematics and Computation
M1 - 128026
ER -