[关键词]
[摘要]
传统无位置传感器控制系统的位置信息处理一般采用PI调节器。针对PI调节器存在参数整定、跟踪性能差和抑制干扰能力弱等问题,提出了一种新型的自适应Luenberger观测器。利用脉振高频电流注入法(HFI)获得高频位置信号,根据电机的动力学方程建立Luenberger观测器并对速度、负载扰动进行观测,采用神经网络建立参数自整定的控制器取代观测器中的PID控制,实现了永磁同步直线电机(PMLSM)的无位置传感器控制。仿真结果表明,在速度变化与负载扰动同时存在的情况下,基于自适应Luenberger观测器的PMLSM控制系统的速度估算误差最大值为2×10-3m/s,位置估算误差最大值为-3×10-5rad,具有良好的跟踪性能和抗干扰性能。
[Key word]
[Abstract]
Traditional position sensorless control systems generally adopt PI regulator for position information processing. A new adaptive Luenberger observer is proposed to solve the drawbacks of PI regulator such as parameter setting, poor tracking performance and weak interference suppression ability. This method uses pulsating high frequency current injection method to obtain the high frequency pulse vibration position signal, and then establishes Luenberger observer for speed and load disturbances according to the dynamic equation of the motor. Neural network is adopted to build the autotuning parameters controller for replacing the PID controller in Luenberger observer. The control of permanent magnet linear synchronous motor (PMLSM) without position sensor is realized. The simulation results show that the maximum error of velocity estimation is 2×10-3m/s,and the maximum error of position estimation is -3×10-5rad. PMLSM control system based on the adaptive Luenberger observer has good tracking performance and antiinterference performance.
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