This paper is concerned with the adaptive event-triggered finite-time pinning synchronization control problem for T-S fuzzy discrete complex networks (TSFDCNs) with time-varying delays. In order to accurately describe discrete dynamical behaviors, we build a general model of discrete complex networks via T-S fuzzy rules, which extends a continuous-time model in existing results. Based on an adaptive threshold and measurement errors, a discrete adaptive event-triggered approach (AETA) is introduced to govern signal transmission. With the hope of improving the resource utilization and reducing the update frequency, an event-based fuzzy pinning feedback control strategy is designed to control a small fraction of network nodes. Furthermore, by new Lyapunov–Krasovskii functionals and the finite-time analysis method, sufficient criteria are provided to guarantee the finite-time bounded stability of the closed-loop error system. Under an optimization condition and linear matrix inequality (LMI) constraints, the desired controller parameters with respect to minimum finite time are derived. Finally, several numerical examples are conducted to show the effectiveness of obtained theoretical results. For the same system, the average triggering rate of AETA is significantly lower than existing event-triggered mechanisms and the convergence rate of synchronization errors is also superior to other control strategies.
This paper investigates the exponential synchronization for T‐S fuzzy complex networks (TSFCNs) with discontinuous activations and mixed time‐varying delays. Based on the IF‐THEN rules, the T‐S fuzzy model of complex networks has been obtained to approximate non‐linear dynamic systems via interpolating certain local linear system. A fuzzy sampled‐data control strategy is designed to achieve exponential stability for the TSFCN by constructing the bilateral time‐dependent Lyapunov–Krasovskii functional. Furthermore, according to the Filippov discontinuity theory, the exponential synchronization criteria of TSFCN with discontinuous activations and mixed time‐varying delays under the linear matrix inequality constraints are obtained. Finally, two numerical simulations are provided to illustrate the effectiveness and feasibility of the proposed method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.