Quantized Stabilization for T-S Fuzzy Systems With Hybrid-Triggered Mechanism and Stochastic Cyber-Attacks

• Published in: IEEE transactions on fuzzy systems Vol. 26; no. 6; pp. 3820 - 3834
• Main Authors: Liu, Jinliang, Wei, Lili, Xie, Xiangpeng, Tian, Engang, Fei, Shumin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Control stability; Control systems; Cybersecurity; Fuzzy systems; Hybrid systems; Hybrid-triggered scheme; Mathematical analysis; Mathematical model; Matrix methods; networked control systems (NCSs); Nonlinear systems; Quantization (signal); Stabilization; stochastic cyber-attacks; Stochastic processes; Symmetric matrices; Takagi–Sugeno (T–S) fuzzy systems; Theorems
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/TFUZZ.2018.2849702

This paper examines quantized stabilization for Takagi-Sugeno (T-S) fuzzy systems with a hybrid-triggered mechanism and stochastic cyber-attacks. A hybrid-triggered scheme, which is described by a Bernoulli variable, is adopted to mitigate the burden of the network. By taking the effect of the hybrid-triggered scheme and stochastic cyber-attacks into consideration, a mathematical model for a closed-loop control system with quantization is constructed. Theorems for main results are developed to guarantee the asymptotical stability of networked control systems by using Lyapunov stability theory and linear matrix inequality techniques. Based on the derived sufficient conditions in theorems, the controller gains are presented in an explicit form. Finally, two practical examples demonstrate the feasibility of designed algorithm.