 New insights on fuzzy sampled-data stabilization of delayed nonlinear systemsRamasamy Saravanakumar, Rupak Datta and Yang Cao Chaos, Solitons & Fractals, 2022, vol. 154, issue C Abstract: This paper explores an improved T-S fuzzy stabilization criteria for nonlinear systems with time-delays via memory sampled-data strategy in the looped-functional context. The sampling period is assumed to be varying within an interval. A new integral inequality is developed to minimize conservatism in the integral term. In addition, free-matrix-based integral inequality (FMBII), and Wirtinger-based integral inequality (WII) are employed. Improved stabilization conditions are derived in linear matrix inequalities (LMIs) using the FMBII, which is based on the looped-functional approach (LFA). A fuzzy memory sampled-data controller design is devised to ensure the asymptotic stability of the closed-loop system. The numerical investigation is carried out with the different approaches, and the resulting outcomes justify that the derived results are less conservative and advantageous over the existing systems. Keywords: Integral inequality technique; Looped-functional; T–S fuzzy control; Variable delay (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:154:y:2022:i:c:s0960077921010080 DOI: 10.1016/j.chaos.2021.111654 Access Statistics for this article Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros More articles in Chaos, Solitons & Fractals from Elsevier |
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