Adaptive NN control of dynamic systems with unknown dynamic friction

Author

Ge, S.S. ; Lee, T.H. ; Wang, J.

Author_Institution

Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore

Volume

2

fYear

2000

fDate

2000

Firstpage

1760

Abstract

Based on the dynamic LuGre friction model, adaptive NN controllers are presented by using neural networks to parameterize the unknown characteristic function α(x, x˙) or the unknown dynamic friction bounding function respectively. Using Lyapunov synthesis, the adaptive control algorithms are designed to achieve globally asymptotic tracking of the desired trajectory and guarantee the boundedness of all the signals in the closed-loop. Intensive simulations are carried out to verify the effectiveness of the proposed methods

Keywords

Lyapunov methods; adaptive control; closed loop systems; control system synthesis; friction; motion control; neurocontrollers; observers; robust control; servomechanisms; Lyapunov synthesis; adaptive neural net control; dynamic LuGre friction model; dynamic systems; globally asymptotic tracking; unknown characteristic function; unknown dynamic friction; Adaptive control; Algorithm design and analysis; Control system synthesis; Control systems; Friction; Network synthesis; Neural networks; Programmable control; Signal design; Signal synthesis;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2000. Proceedings of the 39th IEEE Conference on

Conference_Location

Sydney, NSW

ISSN

0191-2216

Print_ISBN

0-7803-6638-7

Type

conf

DOI

10.1109/CDC.2000.912116

Filename

912116