摘要
提出基于小波神经网络的永磁同步电机无速度传感器控制方法。依据直接检测得到的电流、磁链等参数,基于小波神经网络的时频局部特性、变焦特性、自学习、自适应、鲁棒性及很强的非线性逼近能力的特性,利用小波神经网络建立非线性映射,估计转子位置并计算转子的输出速度,实现电机无速度传感器控制。在Matlab/Simunlink仿真环境下进行仿真研究,仿真结果表明,具有较好的动态响应和鲁棒性。
The method of speed sensorless control of permanent magnet synchronous motor based on wavelet neural networks was put forward.As the wavelet neural network has the properties of local time-frequency characteristics,zooming index,adaptive study,strong robustness and non-linear approaching,according to the parameters of current and flux directly obtained,the non-linear reflection was built to estimate the output speed of rotor and realize the speed sensorless control.The sensorless control was studied in the simulation environment Matlab/Simulink and the result shows the control strategy has good dynamic response and robustness.
出处
《微电机》
北大核心
2010年第7期53-56,共4页
Micromotors
基金
国家自然科学基金(50805049)
广东工业大学校博士启动项目(073030)支助
关键词
永磁同步电机
小波神经网络
无速度传感器
非线性映射
Permanent magnet synchronous motor
Wavelet neural networks
Speed sensorless
Non-linear reflection
