In this paper, the fault estimation problem is studied for a class of nonlinear networked control systems with imperfect measurements. A novel measurement model is proposed to take time-varying delays, random packet dropouts, and the packetdropout compensation into consideration simultaneously. After properly augmenting the states of the original system and the fault estimation filter, the addressed fault estimation problem is converted into an auxiliary H• filtering problem for a stochastic parameter system. In terms of matrix inequalities, a sufficient condition for the existence of the fault estimation filter is derived that depends on the packet dropout rate, the upper and lower bounds of time delays, and the size of the consecutive packet dropouts. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.Theorem 2. For a given scalar g > 0, the filtering error system (12) is stochastically stable and the H• performance constraint (13) is satisfied for all nonzero w(k), if there exist symmetric matrices P1 > 0, P3 > 0, Q1 > 0, Q2 > 0, and Q3 > 0;
This article investigates the fault detection problem in finite-frequency domain for a class of nonlinear networked systems under stochastic cyber-attacks.A novel adaptive event-triggered scheme is introduced to mitigate the transmission burden of the network. A unified measurement model is proposed to take the randomly occurring cyber-attacks and the transmission delays into account simultaneously. Under the consideration of fault sensitivity and disturbance robustness, the addressed fault detection problem is converted into an auxiliary H − ∕H ∞ filtering problem by properly augmenting the states of the original system and the fault detection filter. Intensive stochastic analysis is carried out to obtain sufficient conditions for the existence of the desired fault detection filter, and the corresponding optimal filter parameters can be easily derived by solving a convex optimization problem. Finally, an illustrative example is presented to show the effectiveness and applicability of the proposed method.
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