Adaptive event‐triggered fault detection for nonlinear networked systems in finite‐frequency domain under stochastic cyber‐attacks. (14th March 2022)

• Record Type: Journal Article
• Authors: Zhu, Qi; Jiang, Shun; Pan, Feng
• Is Part Of: International journal of adaptive control and signal processing. Volume 36:Number 7(2022)
• Page Start: 1537
• Page End: 1561
• Publication Date: 2022-03-14
• Subjects: adaptive event‐triggered scheme -- fault detection -- finite‐frequency domain -- nonlinear networked systems; Adaptive control systems -- Periodicals; Adaptive signal processing -- Periodicals; 629.836
• DOI: 10.1002/acs.3409
• Languages: English
• ISSNs: 0890-6327

Abstract

Summary: 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.