Further results on fuzzy sampled-data stabilization of chaotic nonlinear systems

• Published in: Applied mathematics and computation Vol. 379; p. 125225
• Main Authors: Xia, Yude, Wang, Jing, Meng, Bo, Chen, Xiangyong
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 15.08.2020
• Subjects: Chaotic nonlinear systems; Lyapunov-Krasovskii functional method; Robust stabilization; Sampled-data control; Sampled-data control; Lyapunov-Krasovskii functional method; Robust stabilization; Chaotic nonlinear systems
• ISSN: 0096-3003; 1873-5649
• DOI: 10.1016/j.amc.2020.125225

•The fuzzy stabilization of CSs is investigated via a sampled-data strategy;•The cost-efficient sampled data controller is designed;•Contrasted with the existing results, our developed one is less conservative. This work focuses on addressing the sampled-data stabilization problem for chaotic nonlinear systems, where the Takagi-Sugeno (T-S) fuzzy model is employed to dispose of the nonlinearity in the system as well as the controller. Contrasted to the traditional control strategy, a more practical piecewise sampled-data controller is developed, where the input delay during the signal transmission is considered. By introducing an approved method for processing fuzzy items and a novel Lyapunov-Krasovskii functional which is inspired by the Wirtinger inequality, as well as an advanced inequality derivation technique, some sufficient conditions with less conservatism are put forward. Appropriate controller gains can be acquired via the solution of the convex optimization problem. At last, the advantages and feasibility of the method proposed are explained by two numerical examples.