控制理论(社会学)
同步(交流)
计算机科学
人工神经网络
非线性系统
指数稳定性
方案(数学)
芝诺悖论
控制器(灌溉)
控制(管理)
数学
人工智能
生物
数学分析
频道(广播)
物理
几何学
量子力学
计算机网络
农学
作者
Wei Zhu,Dandan Wang,Lu Liu,Gang Feng
出处
期刊:IEEE transactions on neural networks and learning systems
[Institute of Electrical and Electronics Engineers]
日期:2018-08-01
卷期号:29 (8): 3599-3609
被引量:106
标识
DOI:10.1109/tnnls.2017.2731865
摘要
This paper investigates exponential stabilization of continuous-time dynamic systems (CDSs) via event-based impulsive control (EIC) approaches, where the impulsive instants are determined by certain state-dependent triggering condition. The global exponential stability criteria via EIC are derived for nonlinear and linear CDSs, respectively. It is also shown that there is no Zeno-behavior for the concerned closed loop control system. In addition, the developed event-based impulsive scheme is applied to the synchronization problem of master and slave memristive neural networks. Furthermore, a self-triggered impulsive control scheme is developed to avoid continuous communication between the master system and slave system. Finally, two numerical simulation examples are presented to illustrate the effectiveness of the proposed event-based impulsive controllers.
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