Affine matched parameterization approach to sampled-data stabilization criteria for T-S fuzzy systems with variable sampling. Issue 7 (May 2021)

• Record Type: Journal Article
• Authors: Jin, Yongsik; Kwon, W.; Lee, S.M.
• Is Part Of: Journal of the Franklin Institute. Volume 358:Issue 7(2021)
• Page Start: 3530
• Page End: 3553
• Publication Date: 2021-05
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2021.02.023
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: This paper presents new parameterized sampled-data stabilization criteria using affine transformed membership functions for T-S fuzzy systems. To deal with the sampled control input having aperiodic sampling intervals, the proposed method adopts new looped functionals, and employs a modified free weighting matrix inequality. A relaxed condition for the controller design is derived by formulating the constraint conditions of the membership functions in the proposed controller with affinely matched weighting parameter vectors. Based on a newly devised lemma for handling affinely matched vectors, the stabilization and guaranteed cost performance criteria are given in terms of linear matrix inequalities (LMIs). The superiority of the presented method is demonstrated via significantly improved results in numerical examples.