异步电机参数辨识及自整定控制系统研究

发布时间：2018-03-05 05:22

  本文选题：异步电机　切入点：最小二乘法　出处：《浙江大学》2015年硕士论文　论文类型：学位论文

【摘要】：近年来,随着电力电子技术、计算机控制技术的发展,交流伺服控制在伺服控制领域逐渐占据了主导地位,异步电机也随之得到了广泛的应用。因此,针对异步电机高性能控制的研究具有重要的意义。在很多异步电机应用场合中,负载的转动惯量是电机转子的数倍甚至数十倍,其变化对电机系统的动态性能有较大的影响。本文从转动惯量辨识出发,将参数辨识与参数自整定结合,研究能够适应负载转动惯量频繁变化的参数自整定系统。 本文从最小二乘法出发,采用了带反馈的改进型递推最小二乘辨识法,通过引入重初始化和逻辑判断单元检测辨识算法输出,在待辨识量变化时触发重初始化,彻底消除旧观测数据影响。与原恒定遗忘因子的方法相比,一方面能够大幅提高动态响应速度,另一方面也能避免因遗忘因子选择不当而造成辨识结果波动。该算法可以更快地跟踪时变参数,缩短波动时间,提高辨识性能。 基于本文的转动惯量辨识方法,从异步电机的数学模型出发,可将电机以速度环为外环的双闭环结构简化为典型Ⅱ型系统,进而利用工程上常用的参数选择法,建立系统转动惯量与速度环PI参数的联系,利用转动惯量辨识结果自动调整PI控制参数,实现参数自整定。对于负载转动惯量频繁变化的电机系统,该自整定策略能够显著提高系统动态稳态性能。 本文首先在Simulink环境下对异步电机转动惯量参数辨识与参数自整定进行了仿真研究,在此基础上采用dSPACE半实物仿真平台,搭建外围电路,进行了空载起动、突加突减负载等实验,实验结果表明所述理论正确,且在负载转动惯量频繁变化的场合具有较高的实用价值。
[Abstract]:In recent years, with the development of power electronics and computer control technology, AC servo control has gradually occupied a dominant position in the servo control field, and the asynchronous motor has been widely used. The research on high performance control of asynchronous motor is of great significance. In many applications of asynchronous motor, the moment of inertia of load is several times or even tens times of that of motor rotor. In this paper, starting from the moment of inertia identification, the parameter identification and parameter self-tuning are combined to study the parameter self-tuning system, which can adapt to the frequent change of the load moment of inertia. Based on the least square method, an improved recursive least squares identification method with feedback is used in this paper. By introducing reinitialization and logic judgement unit to detect the output of identification algorithm, the reinitialization is triggered when the identification quantity changes. Eliminate the influence of the old observation data completely. Compared with the original method of constant forgetting factor, on the one hand, it can greatly improve the dynamic response speed. On the other hand, it can avoid the fluctuation of identification result caused by the improper selection of forgetting factor, and the algorithm can track the time-varying parameters more quickly, shorten the fluctuation time and improve the identification performance. Based on the method of moment of inertia identification in this paper, starting from the mathematical model of asynchronous motor, the double closed loop structure of motor with speed loop as outer ring can be simplified into a typical 鈪，

本文编号：1568923