Title :
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
fDate :
May 31 2011-June 3 2011
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;
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
DOI :
10.1109/DEST.2011.5936620
