Title :
Vector control of hybrid stepping motor position servo system using neural network control
Author :
Laid, Kefsi ; Dianguo, Xu ; Jingzhuo, Shi
Author_Institution :
Dept. of Electr. Eng., Harbin Inst. of Technol., China
Abstract :
To achieve fast four-quadrant operation and smooth starting and acceleration, vector control is used in the design of the stepping motor servo system drive. The control performance of the stepping motor servo system drive still influenced by the uncertainties, such as external load disturbance, nonlinearity and motor parameter variations. Neural network is used as a supervisor to deal with nonlinearity and uncertainties of the system. Here, we propose a control strategy which combines the advantages of the integral-proportional (IP) controller, neural network and vector control, for the stepping motor position servo system drive
Keywords :
machine vector control; neurocontrollers; position control; servomotors; stepping motors; two-term control; control performance; external load disturbance; four-quadrant operation; hybrid stepping motor position servo system; integral-proportional controller; motor parameter variations nonlinearity; neural network control; smooth acceleration; smooth starting; system uncertainties; vector control; AC motors; Control systems; DC motors; Machine vector control; Magnetic flux; Neural networks; Open loop systems; Servomechanisms; Servomotors; Uncertainty;
Conference_Titel :
Industrial Electronics Society, 2001. IECON '01. The 27th Annual Conference of the IEEE
Conference_Location :
Denver, CO
Print_ISBN :
0-7803-7108-9
DOI :
10.1109/IECON.2001.976012