This paper is concerned with the problem of reliable mixed H ∞ and passivity-based control for a class of stochastic Takagi-Sugeno (TS) fuzzy systems with Markovian switching and probabilistic time varying delays. Different from the existing works, the H∞ and passivity control problem with probabilistic occurrence of time-varying delays and actuator failures is considered in a unified framework, which is more general in some practical situations. The main aim of this paper is to design a reliable mixed H∞ and passivity-based controller such that the stochastic TS fuzzy system with Markovian switching is stochastically stable with a prescribed mixed H∞ and passivity performance level γ > 0 . Based on the Lyapunov-Krasovskii functional (LKF) involving lower and upper bound of probabilistic time delay and convex combination technique, a new set of delay-dependent sufficient condition in terms of linear matrix inequalities (LMIs) is established for obtaining the required result. Finally, a numerical example based on the modified truck-trailer model is given to demonstrate the effectiveness and applicability of the proposed design techniques.

Synthesis of control design is an essential part for vehicle suspension systems. This paper addresses the issue of robust reliable H1 control for active vehicle suspension system with input delays and linear fractional uncertainties. By constructing an appropriate Lyapunov–Krasovskii functional, a set of sufficient conditions in terms of linear matrix inequalities (LMIs) are derived for ensuring the robust asymptotic stability of the active vehicle suspension system with a H1 disturbance attenuation level c. In particular, the uncertainty appears in the sprung mass, unsprung mass, damping and stiffness parame-ters are assumed in linear fractional transformation (LFT) formulations. More precisely, the designed controller is presented in terms of the solution of LMIs which can be easily checked by MATLAB-LMI toolbox. Finally, a quarter-car suspension model is considered as an example to illustrate the effectiveness and applicability of the proposed control strategy. [DOI: 10.1115/1.4028776

In this paper, fault-tolerant sampled-data control for flexible spacecraft in the presence of external disturbances, partial actuator failures and probabilistic time delays is investigated. In particular, unlike the common assumptions on continuous-time information on control input, a more realistic sampled-data communication strategy is proposed with probabilistic occurrence of time-varying delays which is modeled by introducing Bernoulli distributed sequences. The main purpose of this paper is to derive fault-tolerant sampled-data control law which makes the closed-loop system robustly asymptotically stable with a prescribed upper bound of the cost function about its equilibrium point for all possible actuator failures. More precisely, by constructing an appropriate Lyapunov-Krasovskii functional involving the lower and upper bound of the probabilistic time delay, a new set of sufficient conditions are derived in terms of linear matrix inequalities for achieving the required result. Numerical simulations are presented by taking the real parameters to the considered aircraft model, which is not only highlighting the ensured closed-loop performance by the proposed control law, but also illustrates its superior fault tolerance, fast convergence and robustness in the presence of external disturbances and actuator faults when compared with the conventional controller. The simulation result reveals the effectiveness and potential of the proposed new design techniques.

In this article, the problem of robust reliable sampled‐data control for a class of uncertain nonlinear stochastic system with random delay control input against actuator failures has been studied. In the considered system, the parameter uncertainty satisfies the norm bounded condition and the involved time delay in control input are assumed to be randomly time‐varying which is modeled by introducing Bernoulli distributed sequences. By constructing a novel Lyapunov–Krasovskii functional involving with the lower and upper bounds of the delay, a new set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) for ensuring the robust asymptotic stability of the uncertain nonlinear stochastic system with random delay and disturbance attenuation level about its equilibrium point for all possible actuator failures. In particular, Schur complement together with Jenson's integral inequality is utilized to substantially simplify the derivation in the main results. The derived analytic results are applied to design robust reliable sampled‐data controller for hanging crane structure model and simulation results are provided to demonstrate the effectiveness of the proposed control law. © 2014 Wiley Periodicals, Inc. Complexity 21: 42–58, 2015

In this article, the problem of reliable gain‐scheduled H∞ performance optimization and controller design for a class of discrete‐time networked control system (NCS) is discussed. The main aim of this work is to design a gain‐scheduled controller, which consists of not only the constant parameters but also the time‐varying parameter such that NCS is asymptotically stable. In particular, the proposed gain‐scheduled controller is not only based on fixed gains but also the measured time‐varying parameter. Further, the result is extended to obtain a robust reliable gain‐scheduled H∞ control by considering both unknown disturbances and linear fractional transformation parametric uncertainties in the system model. By constructing a parameter‐dependent Lyapunov–Krasovskii functional, a new set of sufficient conditions are obtained in terms of linear matrix inequalities (LMIs). The existence conditions for controllers are formulated in the form of LMIs, and the controller design is cast into a convex optimization problem subject to LMI constraints. Finally, a numerical example based on a station‐keeping satellite system is given to demonstrate the effectiveness and applicability of the proposed reliable control law. © 2014 Wiley Periodicals, Inc. Complexity 21: 214–228, 2015