DocumentCode
2130379
Title
Robust fuzzy neural network based control for mechatronic servo systems with high nonlinearity
Author
Sato, Yoshishige ; Kawasaki, Haruhisa
Author_Institution
Graduate Sch. of Eng., Gifu Univ., Japan
fYear
2001
fDate
2001
Firstpage
326
Lastpage
330
Abstract
The intelligent controls such as a neural network based control for mechatronic positioning servo systems have been researched actively in recent years because the mechanism design could not cope with the advanced requirements. This paper proposes a novel robust fuzzy-neural network based control for the mechatronic positioning servo systems that have nonlinear characteristics such as friction, backlash, variations of load and system parameters, and unknown disturbances. Computational simulation results for one-degree-of-freedom positioning system are shown to confirm the validity of the proposed controller
Keywords
electric motors; fuzzy control; machine control; mechatronics; neurocontrollers; nonlinear control systems; robust control; servomechanisms; 1-DOF positioning system; backlash; friction; intelligent controls; load parameters; mechatronic positioning servo systems; nonlinearity; robust fuzzy neural network based control; system parameters; unknown disturbances; Control systems; Friction; Fuzzy control; Fuzzy neural networks; Intelligent control; Mechatronics; Neural networks; Nonlinear control systems; Robust control; Servomechanisms;
fLanguage
English
Publisher
ieee
Conference_Titel
SICE 2001. Proceedings of the 40th SICE Annual Conference. International Session Papers
Conference_Location
Nagoya
Print_ISBN
0-7803-7306-5
Type
conf
DOI
10.1109/SICE.2001.977855
Filename
977855
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