面向直流电机模型时变参数的在线辨识方法

Online Identification Method of Time-Varying Parameters for DC Motors

在直流电机建模优化问题的研究中,由于直流电机的时变参数随现场工况的变化而变化,导致采用离线辨识方法无法估计直流电机的系统模型,针对直流电机系统参数的时变性,提出一种直流电机时变参数的在线辨识策略。依据直流电机的电势平衡方程和转矩平衡方程,得到直流电机的传递函数,转化为电动机角速度和电压之间的差分方程,然后,采用递推最小二乘算法进行在线辨识,从而实现直流电机系统模型在线辨识的目的。搭建直流电机在线辨识系统实验平台,采用改变直流电机载荷的方式,进行了在线实时辨识的实验,实验结果表明:改进方法辨识效果良好,较好地实现了直流电机在参数时变的情况下,辨识效果良好,辨识模型较好地跟踪系统参数的变化。

As parameters of DC motors will change with the （~perating environment, the traditional offline identifi- cation cannot identify the varying model. An online identification method is proposed in this paper based on recursive least mean square algorithm. With the potential balance equation and torque balance equation, the transfer function of the DC motor is deduced. Then the transfer function is transferred to difference equation. An experimental platform is constructed to test the proposed online identification algorithm. The experiment results for different loads show that the proposed online identification method is effective and it can follow the varying system parameters in real time.