A neural method for dynamical hierarchical optimal control of large-scale systems with multiple time delays

Author

Hou, Zeng-Guang ; Bao, Paul ; Han, Jing-Qing

Author_Institution

Inst. of Syst. Sci., Acad. Sinica, Beijing, China

Volume

2

fYear

1998

fDate

4-9 May 1998

Firstpage

1667

Abstract

In the paper, a neural-network-based dynamic solver (LHCNN) is proposed for dynamical hierarchical optimal control of large-scale systems with multiple time delays. The local optimization subnetworks (LONN) and the coordination subnetwork (CNN) constituting the LHCNN can work simultaneously to provide the optimal solutions to the original problems. The LHCNN is globally stable and is inherently easy for implementation

Keywords

delays; hierarchical systems; large-scale systems; neurocontrollers; optimal control; CNN; LHCNN; LONN; coordination subnetwork; dynamical hierarchical optimal control; global stabililty; large-scale systems; local optimization subnetworks; multiple time delays; neural-network-based dynamic solver; Application software; Computer networks; Delay effects; Erbium; Integrated circuit interconnections; Lagrangian functions; Large-scale systems; Neural networks; Optimal control; Optimization methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7576

Print_ISBN

0-7803-4859-1

Type

conf

DOI

10.1109/IJCNN.1998.686029

Filename

686029