|
标题：基于参数辨识的电机驱动系统模型结构判定 |
|
作者：张希月，王璨，杨明，等 |
|
| 2017年第9期 访问次数：298次 |
|
摘要：传统意义上系统参数的辨识均基于一个已知的系统结构，一旦系统结构未知或不精确，就会导致参数辨识的较大误差。本文尝试从逆向思维出发，由参数辨识算法反推模型结构，利用基于最小二乘的双惯量辨识算法获取电机侧转动惯量，与其真实值构建误差评价函数，从而判断驱动系统结构属于单惯量刚性系统或双惯量弹性系统，再利用与模型结构相对应的最小二乘辨识算法，对系统的机械参数进行辨识，实现驱动系统结构与参数的双重优化。
关键词：最小二乘算法；单惯量刚性系统；双惯量弹性系统；误差评价函数；参数辨识
Abstract: In the traditional sense, the identification of system parameters is based on a known system structure. Once the system structure is unknown or inaccurate, it will lead to a large error in parameter identification. In this paper, the model structure was deduced from the parameter identification algorithm. The inertia of the motor was obtained by using the twomass identification algorithm based on the least squares, and the error evaluation function was constructed with the real value, the drive system structure could be judged. For the onemass rigid system and the twomass elastic system, using the corresponding least squares identification algorithm can realize the double optimization of drive system structure and parameters.
Key words: least square method；onemass rigid system；twomass elastic system；error evaluation function；parameter identification |
|
| |
|
