A Simulation and Experimental Study on Identification of an Electromechanical System

T. Kara, Sawsan Abokoos
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引用次数: 1

Abstract

The current applications in electromechanical energy conversion demand highly accurate speed and position control. For this purpose, a better understanding of the motion characteristics and dynamic behavior of electromechanical systems including nonlinear effects is needed. In this paper, a suitable model of Permanent Magnet Direct Current (PMDC) motor rotating in two directions is developed for identification purposes. Model is parameterized and identified via simulation and using real experimental data. Linear and nonlinear models for the system are built for identification, and the effective nonlinearities in the system, which are Coulomb friction and dead zone, are integrated into the nonlinear model. A Weiner- Hammerstein nonlinear system description is used for identification of the model. MATLAB is selected as the investigating tool, and a simulation model is used to observe the error between the simulated and estimated outputs. Identification of the linear and nonlinear system models using experimental data is performed using the least squares (LS) and recursive least squares (RLS) methods. Performance of the model and identification method with the real time experiments are presented numerically and graphically, revealing the advantages of the proposed nonlinear identification approach.
机电系统辨识的仿真与实验研究
目前在机电能量转换中的应用要求高精度的速度和位置控制。为此,需要更好地理解机电系统的运动特性和动态行为,包括非线性效应。本文建立了一种适合永磁直流电动机的双向旋转模型。通过仿真和实际实验数据对模型进行了参数化和辨识。建立了系统的线性和非线性模型进行辨识,并将系统中的有效非线性库仑摩擦和死区集成到非线性模型中。采用Weiner- Hammerstein非线性系统描述法对模型进行辨识。选择MATLAB作为研究工具,通过仿真模型观察仿真输出与估计输出之间的误差。利用最小二乘和递归最小二乘方法对实验数据进行线性和非线性系统模型的辨识。通过实时实验对模型和识别方法的性能进行了数值和图解的说明,揭示了所提出的非线性识别方法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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