Xiaowu Mu

This paper proposes the event-triggered safety-critical control algorithm for uncertain nonlinear system. To deal with the unknown state- and time-dependent disturbance, and a robust intergral of the sign of the error (RISE) disturbance observer is utilized, which can ensure the estimation error exponentially converge to zero. Then, the safety and stability control objectives are transformed into the constraint conditions of quadratic program (QP) by utilizing control barrier function (CBF) and control Lyapunov function (CLF). By applying the event-triggered control mechanism (ETM), the control input is calculated only on event-triggered moments by solving the discrete-time QP with the constraints of safety and stability. The control objectives are achieved in whole time interval, while also enhancing the feasibility of control algorithm and saving calculation resources. Moreover, the Zeno behavior is excluded in the ETM. Finally, numerical simulations validity the proposed control algorithm.

This paper addresses the finite-time H∞ control problem of fuzzy semi-Markovian jump systems with immeasurable premise variables by a new observer-based adaptive event-triggered scheme. More general nonlinear systems can be described by the fuzzy system model since the selected premise variables are dependent on system states. Firstly, our work relaxes the restriction of measurable premise variables of nonlinear plant and the fuzzy observer is designed to estimate unmeasurable system states. Then, our work proposes the new observer-based adaptive event-triggered scheme to better save network resources, which is verified by sufficient comparison experiments in the simulation. Furthermore, a novel method is firstly proposed to deal with the asynchronous problem of premise variables, i.e. the premise variables of nonlinear plant, fuzzy observer and event-triggered controller are asynchronous. By applying the delay system method, free-weighting matrix approach and slack matrix variables, novel sufficient conditions are established to guarantee the finite-time H∞ performance of the closed-loop system, where the nonlinear terms caused by network-induced delay and partly unknown transition rates can be tackled by suitable method. Finally, the single-link robot arm system is presented to demonstrate the efficiency and advantages of the proposed fuzzy control scheme.

In this paper, the secure dual asynchronous tracking control problem is studied for Markov jump systems (MJSs) under hybrid cyberattacks via memory-based event-triggered mechanisms (ETMs). For the first time, both the tracking system (TS) and the reference system (RS) are considered to be MJSs, and a novel dual asynchronous controller is proposed based on hidden Markov model for the case that the mode information of the TS and the RS cannot be accurately received. In order to reduce the redundant data transmission, a novel asynchronous memory-based ETM is designed by introducing two window functions. In addition, considering the openness of network, two independent random variables are introduced to characterize the cyberattacks on tracking system-controller channel and reference system-controller channel respectively. By constructing suitable Lyapunov functionals, sufficient conditions are given to guarantee the stochastic stability and H _∞ performance of the resulted system. Finally, simulation examples are given to verify the effectiveness of the proposed strategy.

This paper investigates the synchronization problem for master‐slave stochastic memristive neural networks (SMNNs) with time‐delay via event‐triggered impulsive control (ETIC). Firstly, a novel ETIC method is designed for SMNNs to realize quasi‐synchronization in mean square sense. Different from time‐triggered impulsive control (TTIC) in the existing results on SMNNs, the proposed event‐triggered method determines impulsive instants based on the real‐time system states, which can reduce redundant impulses. Compared with the existing ETIC for deterministic memristive neural networks (MNNs), the proposed event‐triggered mechanism (ETM) can exclude Zeno behavior completely by adding the waiting time, when stochastic disturbances occur in MNNs. Secondly, if the master SMNNs have nonzero control inputs, an adaptive‐impulsive hybrid controller with ETM is designed to realize almost surely exponential synchronization. Under the ETM, the number of transmitted events is reduced, then control resources can be saved. Zeno behavior can be excluded in almost sure sense. Ultimately, simulations are presented to illustrate the validity of the obtained results.