Closed-loop control of nonlinear neural networks: The estimate of control time and energy cost

被引：20
|
作者：
Chen, Chongyang [1 ]
Zhu, Song [1 ]
Wei, Yongchang [2 ]
机构：
[1] China Univ Min & Technol, Sch Math, Xuzhou 221116, Jiangsu, Peoples R China
[2] Zhongnan Univ Econ & Law, Sch Business Adm, Wuhan 430073, Hubei, Peoples R China
来源：
NEURAL NETWORKS | 2019年 / 117卷
关键词：
Closed-loop control; Nonlinear neural networks; Finite-time; Energy cost; GLOBAL EXPONENTIAL STABILITY; FINITE-TIME; CONTROLLABILITY; SYNCHRONIZATION;
D O I：
10.1016/j.neunet.2019.05.016
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 concentrates on an estimate of the upper bounds for control time and energy cost of a class of nonlinear neural networks (NNs). By constructing the appropriate closed-loop controller u(S) and utilizing the inequality technique, sufficient conditions are proposed to guarantee achieving control target in finite time of the considered systems. Then, the estimate of the upper bounds for the control energy cost of the designed controller u(S) is proposed. Our results provide a new controller which can ensure the realization of finite time control and energy consumption control for a class of nonlinear NNs. Meanwhile, the obtained results contribute to qualitative analysis of some nonlinear systems. Finally, numerical examples are presented to demonstrate the effectiveness of our theoretical results. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码：145 / 151
页数：7
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