Adaptive back-stepping position control system with fuzzy neural networks algorithm

Author

Kim, Han Me ; Park, Kyoung Taik ; Kim, Seock Joon

Author_Institution

Environ. & Energy Res. Div., Korea Inst. of Machinery & Mater., Daejeon, South Korea

fYear

2011

fDate

May 31 2011-June 3 2011

Firstpage

170

Lastpage

175

Abstract

This paper deals with adaptive back-stepping position control system with FNNs(fuzzy neural networks) algorithm for servo system with system uncertainty. The proposed control scheme is induced from the result with the definition of continuative LCF(Lyapunov control functions). In addition, to guarantee the stability problem of the proposed control scheme, the connection weight vector of the FNNs is updated by adaptive rule. The effectiveness of the adaptive back-stepping control system with the FNNs was compared with that of the standard back-stepping control system through computer simulation.

Keywords

Lyapunov methods; adaptive control; fuzzy neural nets; neurocontrollers; position control; servomechanisms; Lyapunov control functions; adaptive back-stepping position control system; fuzzy neural networks algorithm; servo system; stability problem; Adaptive systems; Friction; Fuzzy control; Fuzzy neural networks; Servomotors; Uncertainty; Adaptive back-stepping; fuzzy neural networks; nonlinear friction;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Ecosystems and Technologies Conference (DEST), 2011 Proceedings of the 5th IEEE International Conference on

Conference_Location

Daejeon

Print_ISBN

978-1-4577-0871-8

Type

conf

DOI

10.1109/DEST.2011.5936620

Filename

5936620