Network-based fuzzy control for nonlinear Markov jump systems subject to quantization and dropout compensation

• Published in: Fuzzy sets and systems Vol. 371; pp. 96 - 109
• Main Authors: Zhang, Meng, Shi, Peng, Ma, Longhua, Cai, Jianping, Su, Hongye
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.09.2019
• Subjects: [formula omitted] control; Fuzzy systems; Markov jump systems; Packet dropout; H∞ control; Markov jump systems; Fuzzy systems; Packet dropout
• ISSN: 0165-0114; 1872-6801
• DOI: 10.1016/j.fss.2018.09.007

This paper focuses on the issue of network-based fuzzy control for nonlinear Markov jump systems with unreliable communication links. The nonlinear system under consideration is described by a Takagi–Sugeno (T–S) fuzzy model through corresponding fuzzy rules. The control signals are quantized by a logarithmic quantizer before they are transmitted to the network, and in case quantized control signals lose intermittently when being passed to the actuator, a compensation strategy is implemented to deal with the packet dropout. Based on a novel Lyapunov function which is both fuzzy-basis-dependent and mode-dependent, the existence criterion for the desired controller is established to ensure the stochastic stability as well as a predefined H∞ performance index of the resulting closed-loop system. A bench mark example of robot arm is presented to demonstrate the validity of the proposed design technique.