In practical robust design applications, a second-order polynomial model is adequate to accommodate the curvature of process mean and variance functions, thus mean-squared robust design models, frequently used by many researchers, would contain fourth-order terms.
This article studies mean square robust stability problem for stochastic switched linear discrete systems with convex polytopic uncertainties with interval time-varying delays.
This article is concerned with mean square robust stability of stochastic switched discrete time-delay systems with convex polytopic uncertainties.
By using improved Lyapunov-Krasovskii functionals combined with LMIs technique, we propose new criteria for the mean square robust stability of the system.
Second, the approach allows us to design the switching rule for mean square robust stability in terms of LMIs, which can be solvable by utilizing Matlab's LMI Control Toolbox available in the literature to date.
Switching rule for the mean square robust stability is presented in Section 3. Numerical example is provided to illustrate the theoretical results in Section 4, and the conclusions are drawn in Section 5.
Based on the discrete Lyapunov functional, a switching rule for the mean square robust stability for the stochastic switched system with convex polytopic uncertainties is designed via linear matrix inequalities.
This article has proposed a switching design for the mean square robust stability of stochastic switched linear discrete-time systems with convex polytopic uncertainties with interval time-varying delays.
Based on the discrete Lyapunov functional, a switching rule for the mean square robust stability for the stochastic system with convex polytopic uncertainties is designed via linear matrix inequalities.
Minimum mean-squared error.
Rq = root mean square roughness.
