This paper is concerned with the problem of designing fuzzy controllers for a class of nonlinear dynamic systems. The considered nonlinear systems are described by T-S fuzzy models with nonlinear local models, and the fuzzy models have fewer fuzzy rules than conventional T-S fuzzy models with local linear models. A new fuzzy control scheme with local nonlinear feedbacks is proposed, and the corresponding control synthesis conditions are given in terms of solutions to a set of linear matrix inequalities (LMIs). In contrast to the existing methods for fuzzy control synthesis, the new proposed control design method is based on fewer fuzzy rules and less computational burden. Moreover, the local nonlinear feedback laws in the new fuzzy controllers are also helpful in achieving good control effects. Numerical examples are given to illustrate the effectiveness of the proposed method.

This paper is concerned with reliable control problems of cyber-physical systems against a class of frequency-constrained sensor and actuator attacks. We consider a continuous-time linear physical system equipped with an observer-based abnormal detector, and it is assumed that control signals and partial sensor outputs transmitted via network layers are vulnerable to cyber attacks. With the use of detection mechanisms of the abnormal monitor, an upper bound of the worst stealthy attacks is obtained, which is composed of the information of the detector's threshold, the attack's structure, and frequency characteristic. By exploiting the bound information, a novel attack compensator, which can stabilize the system with a nearly desired system performance, is proposed for a situation where an attack may occur without triggering an alarm. Finally, the effectiveness of the proposed control policy is verified by a numerical example.

The distributed fault-tolerant (FT) consensus control problem of linear multiagents with disturbances is considered in this article. For undirected graphs, first, by introducing adaptive control coefficients, multiagent reliable control can be carried out fully distributed, removing the assumption that global information should be known prior. Furthermore, different from existing consensus FT studies, the limitation of continuous communication among agents is removed by developing an open-loop estimation and event-triggering mechanism (ETM). Particularly, distinct from some dwell-time methods that enforce an interevent time greater than zero at the expense of asymptotic stability, by introducing timer variables, positive interevent time and asymptotic stability can be guaranteed simultaneously by the proposed ETM in the absence of disturbances. Furthermore, a minimum positive trigger interval can be maintained for each agent even in the presence of disturbances, indicating the robustness of the event-triggered strategy. It is demonstrated that the suggested event-triggered control method performs reliable disturbance suppression for all agents in a completely distributed way with intermittent communication while excluding the Zeno behavior. Moreover, we try to generalize our results to directed strong connectivity. Finally, simulation examples are carried out to illustrate the efficacy of the suggested scheme.

This paper focuses on the problem of adaptive fuzzy consensus tracking control with event-triggered input for a class of fractional-order multi-agent systems (FOMASs), where systems are considered to be with unmeasurable states, mismatched uncertain external disturbances and unknown nonlinearities. An event-triggered mechanism with a decreasing threshold function is proposed in this paper, which mitigates communication burden and avoids large control impulse. To achieve better tracking performance in distributed control strategy, a compensating fractional-order adaptation law associated with consensus tracking error is introduced when agents can not obtain the information of reference trajectory directly. Under the fractional-order stability theory, a novel distributed adaptive event-triggered controller with fuzzy observers is constructed, which ensures the boundedness of tracking errors. A simulation example demonstrates the correctness of the presented scheme.

This paper is concerned with the fault isolation problem for T-S fuzzy systems with sensor faults. With the help of a set theoretic description of T-S fuzzy models, a new fault isolation scheme is proposed. It consists of a set of fuzzy observers and each of them corresponds to a specified sensor, where the antecedent and consequent parts of the observer are independent on the sensor output. Different from the existing approaches, the premise variables, which do not depend on the specified sensor output but depend on the other sensor outputs, are used in the proposed observer, which has the potential to lead to a better fault isolation performance. In the end, an example is given to show the effectiveness of the fault isolation method.