Fixed-time stabilization for impulsive neural networks

被引：0

作者：

Nowakowski, Andrzej ^{[1
]}

Matusik, Radoslaw ^{[1
]}

Michalak, Anna ^{[2
]}

机构：

[1] Univ Lodz, Fac Math & Comp Sci, Lodz, Poland

[2] Univ Lodz, Fac Econ & Sociol, Lodz, Poland

来源：

2023 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, IJCNN | 2023年

关键词：

fixed-time; synchronization; impulses; neural network; control theory; dynamic programming; FINITE-TIME; STABILITY; SYNCHRONIZATION;

D O I：

10.1109/IJCNN54540.2023.10191195

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents finite-time and fixed-time stabilization for impulsive neural networks, for which a kind of optimal control problem was investigated. A new method based on dual dynamic programming was applied. A verification theorem for finite-time and fixed-time stability was proved. Additionally, numerical algorithms were presented, which demonstrate that impulses are necessary for achieving finite-time stability in neural networks.

引用

页数：8

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