Event-triggered filtering and fault estimation for nonlinear systems with stochastic sensor saturations

Abstract

This paper is concerned with the filtering problem for a class of nonlinear systems with stochastic sensor saturations and event-triggered measurement transmissions. An event-triggered transmission scheme is proposed with hope to ease the traffic burden and improve the energy efficiency. The measurements are subject to randomly occurring sensor saturations governed by Bernoulli distributed sequences. Special effort is made to obtain an upper bound of the filtering error covariance in the presence of linearization errors, stochastic sensor saturations as well as event-triggered transmissions. A filter is designed to minimize the obtained upper bound at each time step by solving two sets of Riccati-like matrix equations, and thus the recursive algorithm is suitable for online computation. Sufficient conditions are established under which the filtering error is exponentially bounded in mean square. The applicability of the presented method is demonstrated by dealing with the fault estimation problem. An illustrative example is exploited to show the effectiveness of the proposed algorithm.

Finite‐horizon fault estimation for time‐varying systems with multiple fading measurements under torus‐event–based protocols

“…Theorem 1. Consider the discrete time-varying system (9) subject to the multiple fading measurements governed by the torus-event-based protocols (4). For a given positive scalar > 0, a positive definite matrix W and two positive scalars 1 and 2 , index (10) is satisfied if there exist a series of positive definite matrices P t and parameter pairs (G t , K t ) satisfying the following discrete time-varying RDE:…”

“…Theorem 3. Consider the discrete time-varying system (9) subject to the multiple fading measurements governed by the torus-event-based protocols (4). Let the disturbance attenuation level > 0, the positive definite matrix W > 0, and two positive scalars 1 > 0 and 2 > 0 be given.…”

“…Remark 3. In this paper, the finite-horizon H ∞ fault estimation issue is dealt with for a class of discrete time-varying systems subject to multiple fading measurements governed by the torus-event-based protocols (4). It can be obtained from the design of estimator algorithm that all the essential factors resulting in the system complexities have been embodied during the desired estimator design procedure, which contain (1) the probabilities of randomly occurring faults, (2) the matrices of time-varying system, (3) the statistic information of multiple fading measurements, and (4) the thresholds of torus-event-based protocols.…”

“…With the improvement of security and reliability of modern control system, the fault detection and fault tolerant control issues have received a steadily growing research interest over the last few years. [1][2][3][4] As is known to all, the aim of fault detection is to detect the occurred faults and give timely alarms. It is difficult to obtain the quantitative information of fault.…”

Unscented Kalman filtering for nonlinear systems with sensor saturation and randomly occurring false data injection attacks

“…Phenomenon of the saturation usually happens in practical physical systems, which seriously affects system performance and even makes the filter unstable [15–18]. Thus, the saturation problem has been considered for state estimation problems in some existing literatures [19–23]. In [19], the sensor saturation issue for discrete‐time Markovian jump systems has been taken into account in designing fault detection filters.…”