Title
Nonstationary Filtering for Fuzzy Markov Switching Affine Systems With Quantization Effects and Deception Attacks
Abstract
This article focuses on the issue of nonstationary filtering for uncertain fuzzy Markov switching affine systems (FMSASs) with quantization effects and deception attacks (DAs). The resulting FMSASs are comprised of Markov switching piecewise-affine systems over a set of operating regions. To characterize the multinetwork-induced constraints, the measurement output is quantized before being transmitted, and a compensation scheme is applied to tackle the quantized measurement output loss intermittently. Meanwhile, the randomly occurring DAs are involved, in which the attack behaviors are identified by the bounded stochastic signals. Differently, to deal with the multinetwork-induced constraints, a novel nonstationary region-dependent affine filter strategy is developed. By resorting to a mode-dependent and region-dependent Lyapunov functional and S-procedure theory, sufficient conditions are elicited such that the filtering error system is mean-square exponentially stable. Finally, the practicability of the derived results is verified by a practical tunnel diode circuit model.
Year
DOI
Venue
2022
10.1109/TSMC.2022.3147228
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Keywords
DocType
Volume
Deception attacks (DAs),fuzzy Markov jump affine systems,packet dropouts,quantization effects
Journal
52
Issue
ISSN
Citations 
10
2168-2216
0
PageRank 
References 
Authors
0.34
26
4
Name
Order
Citations
PageRank
Jun Cheng153643.22
Yuyan Wu200.34
Zhengguang Wu33550137.72
Huaicheng Yan410.69