In this study, the stability and stabilization analyses are discussed for Takagi-Sugeno (T-S) fuzzy systems with input saturation. A fuzzy-based sampled-data control is designed to stabilize the T-S fuzzy systems. Based on the Lyapunov method and some integral inequality techniques, a set of sufficient conditions is obtained as linear matrix inequality (LMI) constraints to guarantee the asymptotic stability of the considered system. In this process, the linear switching method is utilized to design a controller that is dependent on the membership function, and an integral inequality is utilized. Additionally, determination of the controller parameters is achieved by resolving a series of LMI constraints. The effectiveness of these criteria is demonstrated through a real system that is modeled by the T-S system.

This paper proposes an improved estimation of the reachable set (RS) analysis in linear systems with polytopic uncertainties, peak-bounded inputs and time-varying delay. Inspired by past literature, Lyapunov-Krasovskii's functionals are dealt for treating the time-delay and bounding analysis effectively. So, the proposed method focuses on Lyapunov-Krasovskii's functionals via various time-delay conditions for linear systems. Based on the Lyapunov method, some integral inequalities, useful zero equalities, and the augmented zero equality approach are introduced. The results are expressed in terms of linear matrix inequalities, which are easy to get optimized solutions for obtaining guaranteed minimum RS of system dynamics. Finally, two numerical examples are shown to judge that the proposed estimation method can lead to less conservative results.