Event-triggered fuzzy filtering for nonlinear networked systems with dynamic quantization and stochastic cyber attacks. (February 2022)

• Record Type: Journal Article
• Authors: Li, Zhi-Min; Xiong, Jun
• Is Part Of: ISA transactions. Volume 121(2022)
• Page Start: 53
• Page End: 62
• Publication Date: 2022-02
• Subjects: Nonlinear networked systems -- T–S fuzzy systems -- Dynamic quantization -- Cyber attacks -- Event-triggered filtering; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2021.03.034
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: In this article, the H ∞ filtering issue is considered for discrete-time nonlinear networked systems subject to event-triggered communication scheme, dynamic quantization, and stochastic cyber attacks. The considered nonlinear networked system is described by the Takagi–Sugeno (T–S) fuzzy model. The event-triggered policy and the dynamic quantizer will be considered to realize the effective use of the restricted network bandwidth resources. Moreover, a stochastic variable that satisfies the Bernoulli random binary distribution is employed to characterize the effects of stochastic cyber attacks. This paper focus on the design of full- and reduced-order event-triggered H ∞ filters and the dynamic parameter of the quantizer such that the filtering error system is stochastically stable and satisfies a predefined H ∞ filtering performance. The sufficient design conditions for the event-triggered H ∞ filters and the dynamic parameter of the quantizer are proposed based on linear matrix inequalities (LMIs). Finally, an example based on practical application will be used to verify the effectiveness of the presented design methods. Highlights: The H ∞ filtering problem has been considered for nonlinear networked systems. A feasible online adjusting strategy is proposed for the quantizer's dynamic parameter. The corresponding design conditions are proposed in the form of LMIs.