控制理论(社会学)
同步(交流)
滑模控制
整体滑动模态
控制器(灌溉)
人工神经网络
计算机科学
模式(计算机接口)
李雅普诺夫函数
线性矩阵不等式
Lyapunov稳定性
数学
控制(管理)
数学优化
拓扑(电路)
非线性系统
物理
人工智能
组合数学
操作系统
生物
量子力学
农学
作者
Jing-Jing Xiong,Guobao Zhang,Junxiao Wang,Tianhong Yan
出处
期刊:IEEE transactions on neural networks and learning systems
[Institute of Electrical and Electronics Engineers]
日期:2020-06-01
卷期号:31 (6): 2209-2216
被引量:42
标识
DOI:10.1109/tnnls.2019.2927249
摘要
This brief further explores the problem of finite-time synchronization of delayed recurrent neural networks with the mismatched parameters and neuron activation functions. An improved sliding mode control approach is presented for addressing the finite-time synchronization problem. First, by employing the drive-response concept and the synchronization error of drive-response systems, a novel integral sliding mode surface is constructed such that the synchronization error can converge to zero in finite time along the constructed integral sliding mode surface. Second, a suitable sliding mode controller is designed by relying on Lyapunov stability theory such that all system state trajectories can be driven onto the predefined sliding mode surface in finite time. Moreover, it is found that the presented control approach can be conveniently verified and does not need to solve any linear matrix inequality (LMI) to guarantee the finite-time synchronization of delayed recurrent neural networks. Finally, three numerical examples are exploited to demonstrate the effectiveness of the presented control approach.
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