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

页码：477 / 481

页数：5

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