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Exponential H∞ stabilization of uncertain neural networks with time-varying delay and external disturbance via periodically intermittent control

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This paper is concerned with the exponential H ∞ stabilization for a class of uncertain neural networks with interval time-varying delay and external disturbance via periodically intermittent control. By constructing… Click to show full abstract

This paper is concerned with the exponential H ∞ stabilization for a class of uncertain neural networks with interval time-varying delay and external disturbance via periodically intermittent control. By constructing a novel Lyapunov–Krasovskii functional (LKF) and applying some inequality techniques, delay-dependent sufficient conditions are derived to guarantee the exponential H ∞ stabilization of the considered closed-loop system. These conditions are given in the form of linear matrix inequalities (LMIs). The intermittent state-feedback controller can reduce the effect of external disturbance to a prescribed attenuation level γ . Furthermore, the desired controller gain matrix can be obtained by solving the obtained LMIs. Finally, numerical simulations are given to show the effectiveness and the benefits of the proposed method.

Keywords: uncertain neural; control; exponential stabilization; external disturbance

Journal Title: Transactions of the Institute of Measurement and Control
Year Published: 2022

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