Resilient State and Fault Estimation for Stochastic Nonlinear Systems Under Dynamic Event-Triggered Schemes
This paper focuses on the joint non-fragile state and fault estimation issue for a class of stochastic nonlinear systems under the dynamic event-triggered transmission scheme (DETS). To better conform to practical engineering scenarios, we consider an additive fault whose second-order difference is piecewise zero. A zero-mean matrix with bounded covariance is adopted to characterize the phenomenon of random gain variation. The threshold parameter of the DETS is adjustable via a given dynamic equation, rather than being fixed. By extending the original state with the fault and its first-order difference, the original system is converted into a stochastic parameter one. Accordingly, the goal of this paper is to design a non-fragile filter, which ensures an upper bound (UB) for the filtering error covariance (FEC) represented by specific matrix difference equations; thereafter, the gain parameter is determined by minimizing the acquired UB. Subsequently, a sufficient condition is derived regarding the mean-square boundedness of the filtering error. Finally, a numerical example is given to confirm the effectiveness of our estimation algorithm.