Application of neural network to hierarchical optimal control of the class of continuous time-varying large-scale systems

被引：0
|
作者：
Xie, SM [1 ]
Huang, JW [1 ]
Zhao, CJ [1 ]
Xu, ZL [1 ]
机构：
[1] Tsing Hua Univ, Sch Econ & Management, Beijing 100084, Peoples R China
来源：
1997 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT PROCESSING SYSTEMS, VOLS 1 & 2 | 1997年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we give a new method of applying neural network to the hierarchical control problem of a class of continuous time-varying large-scale systems. we assume that the continuous-time system is linear time-varying, and disturbed by additive white noises, and the state informations at the sampling instants incomplete, and the continuous-time criteria are quadratic. A two-level connectional network of novel architecture is designed for the optimal control problem of large-scale systems. Circuits to solve these problems are designed using deneral principle.
引用
收藏
页码：477 / 481
页数：5
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