Event-Triggered Dynamic Output Quantization Control of Switched T–S Fuzzy Systems With Unstable Modes
Xinsong Yang, Guoying Feng, Changtao He, Jinde Cao
Abstract
This article is concerned with exponential stabilization almost surely for a class of discrete-time switched T–S fuzzy systems (DTSTSFSs), in which each mode switches according to transition probability and evolves with mode-dependent average dwell time. Parallel distributed compensation (PDC) event-triggered dynamic output quantization (ETDOQ) control is considered for the DTSTSFSs, where event-triggered (ET) mechanism without Zeno behavior is designed, which is mode-dependent and does not restrict the dwell time of each mode. By using the mode-dependent Lyapunov function method, two sufficient conditions termed by linear matrix inequalities are provided. Different from most of existing results, no inequality is resorted in dealing with the uncertainties coming from the quantization. It is interesting that the controlled modes are not required to be stable. New algorithm is designed for the control gains of the ETDOQ controller and the parameters of the ET condition, which overcomes the mismatching difficulty of the parameters induced by the PDC. Numerical simulations demonstrate the merits of the theoretical analysis.