DocumentCode
504764
Title
Adaptive friction observer and sliding mode controller development with RFNN for nonlinear friction compensation
Author
Han, Seong Ik ; Cho, Young Su ; Jin, Seong Min ; Lee, Chang Don ; Yang, Soon Yong
Author_Institution
Dept. of Electr. Autom., Suncheon First Coll., Cheonnam, South Korea
fYear
2009
fDate
18-21 Aug. 2009
Firstpage
4971
Lastpage
4976
Abstract
In this paper, the adaptive friction compensation schemes are developed to provide much enhanced position tracking performance against nonlinear dynamic friction. The adaptive friction parameter observer possessing a simple structure and to be easy to implementation into controller is first studied to estimate the friction parameters. The process of the uncertainty approximation using the RFNN technique is considered to enhance the positioning performance. Suppressing additional unknown friction uncertainty by the RFNN, the favorable position tracking result can be achieved via some simulation and experiment to the rotary servo mechanical system.
Keywords
adaptive control; compensation; friction; fuzzy neural nets; machine control; neurocontrollers; nonlinear control systems; observers; recurrent neural nets; servomechanisms; uncertain systems; variable structure systems; adaptive friction compensation; adaptive friction parameter observer; friction parameter estimation; friction uncertainty; nonlinear friction compensation; position tracking; recurrent fuzzy neural network; rotary servo mechanical system; sliding mode controller; uncertainty approximation; Adaptive control; Control systems; Friction; Fuzzy control; Fuzzy neural networks; Hysteresis; Neural networks; Programmable control; Servomechanisms; Sliding mode control; Adaptive friction observer; LuGre friction model; Recurrent fuzzy neural networks; Sliding mode control;
fLanguage
English
Publisher
ieee
Conference_Titel
ICCAS-SICE, 2009
Conference_Location
Fukuoka
Print_ISBN
978-4-907764-34-0
Electronic_ISBN
978-4-907764-33-3
Type
conf
Filename
5334646
Link To Document