A hybrid fuzzy logic and neural network controller for spacecraft docking system

Author

Chen Xinhai ; Chen Genshe ; Yang Lixin ; He Shichen

Author_Institution

Coll. of Astronaut., Northwestern Polytech. Univ., Xian, China

Volume

2

fYear

1993

fDate

19-21 Oct. 1993

Firstpage

870

Abstract

A new hybrid fuzzy logic and neural network control architecture is proposed and its application to attitude control of a spacecraft docking system is described. The controller uses fuzzy logic control to construct a knowledge base of control rules and learns by updating its prediction of the physical systems behavior and fine tuning a control knowledge base. It is applicable to control problems for which the analytical models of the process are unknown.<>

Keywords

aerospace control; attitude control; fuzzy control; intelligent control; knowledge based systems; learning (artificial intelligence); neural nets; uncertainty handling; analytical models; approximate reasoning; attitude control; control knowledge base; fuzzy logic; fuzzy logic control; knowledge base; learning; neural network controller; nonlinear control problem; spacecraft docking system; Control systems; Educational institutions; Fuzzy control; Fuzzy logic; Helium; Multi-layer neural network; Neural networks; Power system modeling; Space vehicles; Tin;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on

Conference_Location

Beijing, China

Print_ISBN

0-7803-1233-3

Type

conf

DOI

10.1109/TENCON.1993.320151

Filename

320151