Title :
Study of Fuzzy Controller Based on Neural-network for PMSM Speed Adjustment System
Author :
Wang, Limei ; Tian, Mingxiu
Author_Institution :
Shengyang Univ. of Technol., Shenyang
Abstract :
A fuzzy intelligent controller based on BP neural network is proposed in this paper for permanent magnet synchronous motor (PMSM) speed control. The intelligent controller can remember fuzzy rules by neural network, which has not only the simplicity and the nonlinear control ability of fuzzy control, but also the learning and adaptive functions by using neural network. In the double loop of PMSM speed adjustment system, the hysteresis current regulator is implemented in the current loop and the fuzzy intelligent control scheme is applied in the speed loop. The effectiveness of the proposed controller is verified by simulation. Simulation results show that the proposed controller is superior to the traditional PI controller. It has good dynamic and static characteristics because of its advantage in quick response and good robustness
Keywords :
backpropagation; fuzzy control; intelligent control; machine control; neurocontrollers; permanent magnet motors; synchronous motors; velocity control; BP neural network; PMSM speed adjustment system; adaptive function; backpropagation algorithm; fuzzy control; fuzzy intelligent control; hysteresis current regulator; learning function; permanent magnet synchronous motor; speed control; Control systems; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Intelligent control; Intelligent networks; Intelligent systems; Neural networks; Permanent magnet motors; Velocity control; BP algorithm; PMSM; neural network fuzzy control; robustness;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713074