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

Author

San-Ming, Xie ; Jing-Wei, Huang ; Chun-Jun, Zhao ; Xu, Zhong-Ling

Author_Institution

Sch. of Econ. & Manage., Tsinghua Univ., Beijing, China

Volume

1

fYear

1997

fDate

28-31 Oct 1997

Firstpage

477

Abstract

We present a method for applying a 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, that the state information at the sampling instants is incomplete, and that 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 general principles

Keywords

continuous time systems; large-scale systems; neural net architecture; neurocontrollers; optimal control; time-varying systems; additive white noises; circuit design; continuous time criteria; continuous time varying large scale systems; hierarchical optimal control; linear time varying; neural network; novel architecture; optimal control problem; sampling instants; state information; two level connectional network; Computer networks; Concurrent computing; Control systems; Digital control; Large-scale systems; Matrix decomposition; Neural networks; Optimal control; Sampling methods; Time varying systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4253-4

Type

conf

DOI

10.1109/ICIPS.1997.672827

Filename

672827