摘要
在永磁同步电动机(PMSM)驱动应用中,当负载转动惯量变化时,会对系统的伺服特性造成影响。为达到伺服系统高精度控制良好动、静态特性,需要相应地调整控制器的参数。文章采用模型参考自适应辨识(MRAI)法对系统的转动惯量进行在线估计,并用系统的稳态误差、转速和估计的转动惯量作为神经网络的输入,神经网络的输出用来调整PI控制器的比例增益和积分增益,实现了控制器参数的在线优化调整。仿真结果表明,所提出的方案是有效的,显著地改善了系统的伺服精度。
In permanent magnet synchronous motor （PM SM）drive applications,when the motor load rotational inertia changes, the servo characteristic will cause effects. To obtain good dynamic and static performances, the controller parameters are required adjusting correspondingly. In this paper, to get the rotational inertia, on- line evaluation method based on model reference adaptive identification （M RAI） is developed. Here, the static error, rotational speed and the estimated rotational inertia are served as the input signals of the neural network. And the output variables of the neural network are used to adjust the proportional gain and integral gain of the PI controller, thus the online optimizing adjustment of the controller parameters is implemented. The simulation results show the proposed control scheme is effective. The precision of the servo system is improved.
出处
《组合机床与自动化加工技术》
北大核心
2009年第7期75-77,92,共4页
Modular Machine Tool & Automatic Manufacturing Technique
