Neural model reference adaptive control and application to a BTT-CLOS guidance system

Author

Lightbody, Gordon ; Irwin, George W.

Author_Institution

Dept. of Electr. & Electron. Eng., Queen´´s Univ., Belfast, UK

Volume

4

fYear

1994

fDate

27 Jun-2 Jul 1994

Firstpage

2429

Abstract

In this paper a structure for a direct neural adaptive control scheme is proposed, along with a number of possible techniques with which such a controller could be trained. Finally, a case study example is presented in which a direct neural network controller was developed to improve the control of a bank-to-turn, command-to-line-of-sight (BTT-CLOS) missile. Results from simulation studies are presented to demonstrate the effectiveness of the new technique

Keywords

adaptive control; closed loop systems; missile guidance; model reference adaptive control systems; neural nets; neurocontrollers; BTT-CLOS missile guidance system; closed loop system; direct neural MRAC; model reference adaptive control; neural adaptive control; nonlinear sensitivity modelling; Adaptive control; Control engineering; Control systems; Force control; Function approximation; Gain; Neural networks; Pattern recognition; Programmable control; Stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1901-X

Type

conf

DOI

10.1109/ICNN.1994.374601

Filename

374601