This study examines the problem of fault‐tolerant sliding mode control (SMC) design subject to actuator saturation for a class of Takagi–Sugeno fuzzy systems with time‐varying delay and external disturbances. Our main attention is to propose the fault‐tolerant SMC such that for given any initial condition, the system trajectories are forced to reach the sliding surface within a finite time. On the basis of the SM surface and Lyapunov stability theorem, a new set of sufficient conditions in terms of linear matrix inequalities (LMIs) is established to not only guarantee the passivity and asymptotically stability of the resulting closed‐loop system in the designed sliding surface, but also cover the issues of actuator saturation and performance constraints. Then, the desired gain matrix of the fault‐tolerant SMC is obtained in respect of the previously established LMIs such that the reachability of the predefined sliding surface is ensured. It is worth pointing out that the obtained sufficient conditions can preserve the trade‐off between the maximisation of admissible upper bound of time‐varying delay and enlarging the estimation about the domain of attraction for the closed‐loop system. Eventually, the effectiveness and robustness of the proposed control approach are demonstrated via simulation results.

A nondeterministic actuator fault model-based reliable control design method is presented for the leader-following consensus of a multiagent system (MAS) subject to input time-varying delay and the nonlinear phenomenon through the observer framework. Notably, a more generalized practical actuator fault model is proposed where the faults of each actuator are assumed to occur randomly and the fault rates are characterized by stochastic variables that satisfy certain probability conditions. To trace the leader dynamics, a reliable observer-based state feedback consensus algorithm is developed for the pursuing agents. After that, in light of graph theory and the Lyapunov-Krasovskii stability theorem, the required conditions are achieved to guarantee the leader-following consensus of the considered MAS, and then the corresponding reliable controller design method is proposed. Furthermore, simulations are eventually conducted to exhibit the efficiency of the newly developed control scheme, where it is shown that the obtained conditions guarantee the consensus of the considered MAS in the case of possible actuator faults.

This paper is concerned with the finite-time mixed H_∞ 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 mixed H_∞ and passive performance index is achieved. Moreover, the robust mixed H_∞ and passivity filter design gain matrices can be computed from the obtained LMIs. Furthermore, the developed results unify H_∞ 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.