Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6865698 | Neurocomputing | 2015 | 36 Pages |
Abstract
Interval type-2 (IT2) T-S fuzzy model is a useful tool to represent nonlinear systems subject to parameter uncertainties. This study focuses on designing Hâ controllers of IT2 T-S fuzzy systems via dynamic output feedback strategy. The IT2 fuzzy closed-loop systems are represented as descriptor system form for obtaining stability conditions in terms of linear matrix inequalities (LMIs). Membership-function-independent stability conditions for the IT2 fuzzy closed-loop systems are derived by Lyapunov-based approach. The information of the lower and upper membership functions is employed to introduce several slack matrices in the stability analysis and to further relax the obtained results. Numerical examples are provided to illustrate the effectiveness of the proposed method.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Tao Zhao, Jian Xiao, Hanmin Sheng, Tao Wang,