4.7 Article

Stabilization of nonlinear time-delay systems: Flexible delayed impulsive control

Journal

APPLIED MATHEMATICAL MODELLING
Volume 114, Issue -, Pages 488-501

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2022.10.013

Keywords

Time -delay system; Delayed impulse; Exponential stability; Average impulsive estimation

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This paper studies the stabilization of nonlinear time-delay systems under flexible delayed impulsive control. It provides sufficient conditions for establishing stability property using exponential Lyapunov-Razumikhin functions. The results show that the size of delay in continuous dynamics can be flexible, and there is no magnitude relationship between the delay in continuous flow and impulsive delay. By utilizing the proposed method of average impulsive estimation (AIE), the rate coefficients can be adjusted flexibly, and the impulsive delay can be integrated to ensure the stabilization effect of impulses.
This paper studies the stabilization of nonlinear time-delay systems under flexible delayed impulsive control. Some sufficient conditions are provided for establishing stability prop-erty in terms of exponential Lyapunov-Razumikhin functions. It is shown that the size of delay in continuous dynamics can be flexible. Specially, it can be smaller or larger than the impulsive intervals, and there is no magnitude relationship between the delay in contin-uous flow and impulsive delay. In most existing results, from the impulsive control point of view, the Lyapunov functions were based on the assumption that there was a common threshold at every impulse point. In this study, utilizing the proposed method of average impulsive estimation (AIE), the rate coefficients are flexible, and the impulsive delay can be integrated to guarantee the effect of stabilization of impulses. As an application, the theoretical results are applied to the synchronization of a chaotic neural network, and the impulsive control input is formalized in terms of linear matrix inequalities (LMIs). The ef-ficiency of the derived results is illustrated by two numerical examples.(c) 2022 Elsevier Inc. All rights reserved.

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