The intelligent learning control using single neuron and its application in an industrial boiler

Author

Shu-Ling, Zhang ; Ke-Ming, Xie

Author_Institution

Dept. of Autom., Taiyuan Univ. of Technol., China

Volume

1

fYear

1997

fDate

28-31 Oct 1997

Firstpage

797

Abstract

This paper discusses a practicable, adjustable and highly effective plan. It presents a novel and practical algorithm combing human experience with control methods to form an intelligent controller (IC). This idea is used in the combustion process of an industrial boiler. In this IC, central parameters are determined based on human experience. An industrial boiler is complex, multivariable and uncertain with time delays. A single neuron is used to regulate the control parameters. A new controller is composed of IC and the single neuron (NIC). The single neuron can change the control parameters. The simulation results show the effectiveness of the control algorithm. For a complex plant, it has strong robustness and satisfactory characteristics

Keywords

boilers; combustion; industrial control; intelligent control; learning (artificial intelligence); multivariable control systems; neurocontrollers; robust control; uncertain systems; combustion process; complex plant; control parameter regulation; industrial boiler; intelligent controller; intelligent learning control; multivariable system; neural networks; neurocontrol; robustness; simulation; single neuron; time delays; uncertain system; Artificial neural networks; Automatic control; Boilers; Combustion; Control systems; Humans; Industrial control; Intelligent control; Neurons; Tiles;

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.1997.672899

Filename

672899