摘要
针对多相永磁同步电机具有非线性、强耦合等特点,传统的PID控制和模糊控制均不能达到很好的控制效果问题,依据空间矢量解耦的理论,建立了多相永磁同步电机的数学模型,给出了基于模糊高斯基函数神经网络的多相永磁同步电机调速系统控制方法,并在六相永磁同步电机上做了仿真分析研究。结果表明,该控制方法反应速度较快,无超调,在突加负载后速度也能够很好跟踪给定速度。响应过程中电磁力矩及定子电流基本上无振荡现象,稳态时电磁力矩恒定,对应的六相定子电流为规整正弦波。动静态性能均优于传统的PID控制和模糊控制。
The PID control and fuzzy control system could not attain satisfactory performance because of the nonlinear and strong coupling of multiple phase permanent-magnet synchronous motor. In order to get better performance and eliminate static error in multiple phase permanent-magnet synchronous motor control system, the application of a fuzzy neural network control algorithm based on Gauss function to the control of dual Y shift 30° six-phase permanent-magnet synchronous motor speed is in vestigated in this paper. The mathematical model of dual Y shift 30° six-phase permanent-magnet synchronous motor is developed according to the space vector theories. Simulation results indicate that the proposed control scheme can be effectively used in controlling the speed of six-phase permanent-magnet synchronous motor, and has quick response ,no over shoot and running after primely the scheduled speed when the load is suddenly added to. In the course of response, the electromagnetic torque and stator current basically have non oscillating phenomena, electromagnetic torque is constant in steady state, and the corresponding six-phase stator current is sine wave. The dynamic and static performance are both better than traditional PID control and fuzzy control.
出处
《电机与控制学报》
EI
CSCD
北大核心
2007年第2期111-115,共5页
Electric Machines and Control
基金
湖南省自然科学基金资助项目(05JJ30191)
关键词
多相永磁同步电机
模糊神经网络
高斯基函数
multiple phase permanent-magnet synchronous motor
fuzzy neural network
Gauss function
作者简介
欧阳红林（1965-）,男,博士,副教授,研究领域为电力传动及控制;
成兰仙（1981-）,女,硕士,研究方向为多相电机的智能控制.
