This article investigates the delay‐dependent robust dissipative sampled‐data control problem for a class of uncertain nonlinear systems with both differentiable and non‐differentiable time‐varying delays. The main purpose of this article is to design a retarded robust control law such that the resulting closed‐loop system is strictly (Q, S, R)‐dissipative. By introducing a suitable Lyapunov–Krasovskii functional and using free weighting matrix approach, some sufficient conditions for the solvability of the addressed problem are derived in terms of linear matrix inequalities. From the obtained dissipative result, we deduce four cases namely, H∞ performance, passivity performance, mixed H∞, and passivity performance and sector bounded performance of the considered system. From the obtained result, it is concluded that based on the passivity performance it is possible to obtain the controller with less control effort, and also the minimum H∞ performance and the maximum allowable delay for achieving stabilization conditions can be obtained via the mixed H∞ and passivity control law. Finally, simulation studies based on aircraft control system are performed to verify the effectiveness of the proposed strategy. © 2015 Wiley Periodicals, Inc. Complexity 21: 142–154, 2016

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The problem of reliable sampled‐data control design for uncertain singular fuzzy system with randomly occurring delay and nonlinear actuator failures is studied in this paper. The fault model is composed of two parts in which, linear part stands for the gain missing of actuators that vary with the true control input linearly, while the nonlinear part indicates some bounded nonlinear variation. Moreover, the time delay which encountering in the proposed controller is assumed to be randomly varying and satisfies Bernoulli distributed probabilities. By constructing a proper time‐dependent Lyapunov functional, some novel sufficient conditions are derived in terms of linear matrix inequalities (LMIs) for the existence of robustly stochastically stabilizing reliable sampled‐data controllers. Two simulation examples are given to demonstrate the effectiveness of the proposed method.

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This article presents a fuzzy dynamic reliable sampled-data control design for nonlinear Markovian jump systems, where the nonlinear plant is represented by a Takagi-Sugeno fuzzy model and the transition probability matrix for Markov process is permitted to be partially known. In addition, a generalised as well as more practical consideration of the real-world actuator fault model which consists of both linear and nonlinear fault terms is proposed to the above-addressed system. Then, based on the construction of an appropriate Lyapunov-Krasovskii functional and the employment of convex combination technique together with free-weighting matrices method, some sufficient conditions that promising the robust stochastic stability of system under consideration and the existence of the proposed controller are derived in terms of linear matrix inequalities, which can be easily solved by any of the available standard numerical softwares. Finally, a numerical example is provided to illustrate the validity of the proposed methodology.