A Time Delay Neural Network for Dynamical System Control

被引：1
|
作者：
Xu, X. [1 ,2 ]
Wan, L. M. [3 ]
Wang, X. L. [3 ]
Wang, L. K. [4 ]
Liang, Y. C. [4 ]
机构：
[1] Jilin Univ, Coll Math, 2699 Qianjin St, Changchun 130012, Peoples R China
[2] Singapore MIT Alliance, Singapore 117576, Singapore
[3] PLA, EAAF, Res Inst Gen Dev & Evaluat Equipment, Beijing 100076, Peoples R China
[4] Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China
来源：
2008 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5 | 2008年
关键词：
D O I：
10.1109/FUZZY.2008.4630472
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel time delay neural network is proposed for dynamical system control. In this work, A continuous recurrent neural network with time delay neurons in hidden layer is constructed, and the novel training algorithm and control law independent of delay are developed based on Lyapunov's stability approach. Using the proposed method, the control error converges to a range near the zero point and remains within the domain throughout the course of the execution. The usefulness and validity of the presented algorithm are examined by numerical experiments.
引用
收藏
页码：868 / +
页数：2
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