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Event-triggered controller design of nonlinear discrete-time networked control systems in T-S fuzzy model
Affiliation:1. College of Control Science and Engineering, Bohai University, Jinzhou, Liaoning 121013, China;2. School of Information Science and Engineering, Shaodong Normal University, Jinan 250014,China;3. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Liaoning, Dalian 116024, China;4. Institute of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China
Abstract:This article is concerned with event-triggered fuzzy control design for a class of discrete-time nonlinear networked control systems (NCSs) with time-varying communication delays. Firstly, a more general mixed event-triggering scheme (ETS) is proposed. Secondly, considering the effects of the ETS and communication delays, based on the T-S fuzzy model scheme and time delay system approach, the original nonlinear NCSs is reformulated as a new event-triggered networked T-S fuzzy systems with interval time-varying delays. Sufficient conditions for uniform ultimately bound (UUB) stability are established in terms of linear matrix inequalities (LMIs). In particular, the quantitative relation between the boundness of the stability region and the triggering parameters are studied in detail. Thirdly, a relative ETS is also provided, which can be seen as a special case of the above proposed mixed ETS. As a difference from the preceding results, sufficient conditions on the existence of desired fuzzy controller are derived to ensure the asymptotic stability of the closed-loop system with reduced communication frequency between sensors and controllers. Moreover, a co-design algorithm for simultaneously determining the gain matrices of the fuzzy controller and the triggering parameters is developed. Finally, two illustrative examples are presented to demonstrate the advantage of the proposed ETS and the effectiveness of the controller design method.
Keywords:Networked control systems  Takagi-Sugeno (T-S) fuzzy model  Event-triggered communication scheme  Communication delays  Co-design algorithm
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