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
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;
Conference_Titel :
SICE 2001. Proceedings of the 40th SICE Annual Conference. International Session Papers
Conference_Location :
Nagoya
Print_ISBN :
0-7803-7306-5
DOI :
10.1109/SICE.2001.977855