Exponential stability of nonlinear state-dependent delayed impulsive systems with applications

被引:142
作者
Xu, Zhilu [1 ,2 ]
Li, Xiaodi [1 ,2 ]
Stojanovic, Vladimir [3 ]
机构
[1] Shandong Normal Univ, Sch Math & Stat, Jinan 250014, Peoples R China
[2] Shandong Normal Univ, Ctr Control & Engn Computat, Jinan 250014, Peoples R China
[3] Univ Kragujevac, Fac Mech & Civil Engn, Dept Automat Control Robot & Fluid Tech, Kraljevo 36000, Serbia
基金
中国国家自然科学基金;
关键词
Impulsive system; State-dependent delay; Delayed impulse; Lyapunov method; Exponential stability; FUNCTIONAL-DIFFERENTIAL EQUATIONS; NEURAL-NETWORKS; STABILIZATION; COMPENSATION;
D O I
10.1016/j.nahs.2021.101088
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The exponential stability problem for impulsive systems subject to double state dependent delays is studied in this paper, where state-dependent delay (SDD) is involved in both continuous dynamics and discrete dynamics and the boundedness of it with respect to states is prior unknown. According to impulsive control theory, we present some Lyapunov-based sufficient conditions for the exponential stability of the concerned system. It is shown that the stabilizing effect of SDD impulses on an unstable SDD system changes the stability and achieves desired performance. In addition, the destabilizing effect of SDD impulses is also fully considered and the corresponding sufficient conditions are derived, which reveals the fact that a stable SDD system can maintain its performance when it is subject to SDD impulsive disturbance. As an application, the proposed result can be employed to the stability analysis of impulsive genetic regulatory networks (GRNs) with SDD and the corresponding sufficient conditions are proposed in terms of the model transformation technique and the linear matrix inequalities (LMIs) technique. In order to demonstrate the effectiveness and applicability of the derived results, we give two examples including impulsive GRNs with SDD and the impulsive controller design for the nonlinear system with SDD. (C) 2021 Elsevier Ltd. All rights reserved.
引用
收藏
页数:12
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