Title :
Hybrid stepping motor position servo system with on-line trained fuzzy neural network controller
Author :
Panhai, Wang ; Dianguo, Xu ; Jingzhuo, Shi
Author_Institution :
Dept. of Electr. Eng., Harbin Inst. of Technol., China
Abstract :
A digital signal processor (DSP) based two-phase hybrid stepping motor (HBSM) position servo system with integral-proportional (IP) position controller, vector control and on-line trained fuzzy neural network (FNN) controller is introduced in this paper. First, an optimized torque control mechanism and IP position controller are applied to the HBSM servo drive, but the performance of the control system is still influenced by parameter variations and external disturbances of the plant. To overcome this penalty, then, a fuzzy neural network controller is presented to generate an adaptive signal to preserve favourable module-following characteristics. Simulations and experimental results are provided to demonstrate the working of the proposed controller.
Keywords :
AC motors; control system synthesis; digital control; digital signal processing chips; fuzzy control; fuzzy neural nets; machine vector control; neurocontrollers; optimal control; position control; servomotors; stepping motors; torque control; two-term control; DSP; adaptive signal; controller design; digital signal processor; favourable module-following characteristics; hybrid stepping motor position servo system; integral-proportional position controller; on-line trained fuzzy neural network controller; position servo system; two-phase hybrid stepping motor; vector control; Control systems; Digital signal processing; Digital signal processors; Drives; Fuzzy control; Fuzzy neural networks; Machine vector control; Servomechanisms; Servomotors; Torque control;
Conference_Titel :
IECON 02 [Industrial Electronics Society, IEEE 2002 28th Annual Conference of the]
Print_ISBN :
0-7803-7474-6
DOI :
10.1109/IECON.2002.1185303