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Abstract In this paper, the robust mixed H ∞ and passivity-based control problem is investigated for a class of discrete-time Markov jump nonlinear systems with uncertainties, quantization and time-varying transition probabilities. In addition, the time-varying transition probability matrices in the considered system are described by a polytope set. Further, the measurement size reduction technique is implemented which consists of two factors, namely, the logarithmic quantization and the measurement element selection scheme. In order to reflect the imprecision in controller implementation, the additive controller gain problem is considered. Based on the Lyapunov stability theory, a new set of conditions is derived such that the resulting closed-loop Markov jump system is stochastically stable with a prescribed mixed H ∞ and passivity performance index. Finally, the effectiveness of the proposed control scheme is illustrated by two numerical examples including an application example based on a DC motor device. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

This paper is concerned with the finite-time mixedH∞and passivity performance analysis and filter design for a class of uncertain nonlinear discrete-time Markovian jump systems (MJSs) described by Takagi–Sugeno fuzzy model with nonhomogeneous jump processes. In this paper, the proposed MJSs fuzzy model is formulated with norm-bounded parameter uncertainties and time-varying jump transition probability matrices. In particular, the time-varying transition probability matrices are expressed in respect of a polytope. By constructing a suitable Lyapunov functional, a new set of sufficient conditions is derived in the form of linear matrix inequalities (LMIs) to ensure that the filtering error system is robustly stochastically finite-time bounded and a prescribed mixedH∞and passive performance index is achieved. Moreover, the robust mixedH∞and passivity filter design gain matrices can be computed from the obtained LMIs. Furthermore, the developed results unifyH∞and passive filtering problems in a single framework. Finally, two numerical examples including an application-oriented example are provided to demonstrate the effectiveness of the proposed filter design technique. [ABSTRACT FROM PUBLISHER]

This article investigates the asymptotic stabilization of periodic piecewise time-varying systems with time-varying delay under various cyber attacks, particularly deception and acrlong DoS attacks. The addressed system is reformed into a number of time-varying subsystems based on the time interval for each period. Following that, a state-feedback controller with periodic time-varying gain parameters is developed to solve the stabilization problem. The control design depicts the possibility of the aforementioned cyber attacks with two mutually exclusive stochastic Bernoulli distributed parameters. Then, an augmented Lyapunov-Krasovskii functional with periodically varying matrices is used to determine the conditions for designing the proposed controller that ensures the mean-square asymptotic stability of the addressed system. The results of numerical examples support the conclusion that the proposed method is effective and superior, regardless of the cyber attacks involved.