Title :
Neuro-fuzzy control for pneumatic servo system
Author :
Shibata, S. ; Jindai, M. ; Shimizu, A.
Author_Institution :
Dept. of Mech. Eng., Ehime Univ., Japan
Abstract :
A learning method for acquiring the appropriate fuzzy rules using error back propagation to improve the control performance of a pneumatic servo system is presented. In the proposed method, a criteria is defined and the fuzzy rules are adjusted so as to minimize them using error back propagation. Moreover, differentiation of the coefficient of the plant used in error back propagation is accomplished by the newly established neural network. The proposed method is applied to vertical pneumatic servo systems to prove their effectiveness
Keywords :
backpropagation; fuzzy control; multilayer perceptrons; neurocontrollers; pneumatic control equipment; servomechanisms; control performance; error back propagation; fuzzy rules; learning method; neural network; neuro-fuzzy control; pneumatic servo system; Ambient intelligence; Control systems; Mechanical engineering; Optimal control; Petroleum; Pressure control; Pulse modulation; Robust control; Servomechanisms; Three-term control;
Conference_Titel :
Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE
Conference_Location :
Nagoya
Print_ISBN :
0-7803-6456-2
DOI :
10.1109/IECON.2000.972542
