Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4974082 | Journal of the Franklin Institute | 2017 | 14 Pages |
Abstract
This paper investigates the problem of stabilization for fuzzy sampled-data systems with variable sampling. A novel Lyapunov-Krasovskii functional (LKF) is introduced to the fuzzy systems. The benefit of the new approach is that the LKF develops more information about actual sampling pattern of the fuzzy sampled-data systems. In addition, some symmetric matrices involved in the LKF are not required to be positive definite. Based on a recently introduced Wirtinger-based integral inequality that has been shown to be less conservative than Jensen's inequality, much less conservative stabilization conditions are obtained. Then, the corresponding sampled-data controller can be synthesized by solving a set of linear matrix inequalities (LMIs). Finally, an illustrative example is given to show the feasibility and effectiveness of the proposed method.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Chao Ge, Hong Wang, Yajuan Liu, Ju H. Park,