Identification of Force-Displacement and Force-Current Factors in an Active Magnetic Bearing System

Luis M. Castellanos Molina, A. Bonfitto, A. Tonoli, N. Amati
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引用次数: 8

Abstract

Conventional magnetic bearings are usually operated in differential driving mode. This configuration makes it possible to generate both positive and negative forces. The linearization of this force results in force-current and force-displacement factors, which make the control design easier as it can exploit all the tools of linear control theory. However, the control performance can deteriorate when these factors do not closely match the real plant. This paper presents a procedure to identify the force-displacement and force-current factors in an active magnetic bearing (AMB) system using grey-box modeling. These force factors are obtained for different operating points defined by a range of bias currents. Since the AMB has an unstable open loop nature, a position Proportional-Integral-Derivative (PID) controller is implemented to stabilize the plant. Experimental data are collected exciting the system with a persistent disturbance current. The models tuned with the identified parameters were able to describe the plant dynamics with improved accuracy. The set of identified parameters can be exploited in model-based control approaches by varying energy-efficiently the bias current.
主动磁轴承系统中力-位移和力-电流因素的辨识
传统的磁轴承通常在差动驱动模式下运行。这种配置使得它可以同时产生积极和消极的力量。这种力的线性化导致了力电流和力位移因素,这使得控制设计更容易,因为它可以利用线性控制理论的所有工具。然而,当这些因素与真实植物不紧密匹配时,控制性能可能会下降。本文提出了一种利用灰盒模型识别主动磁轴承系统的力-位移和力-电流因素的方法。这些力因子是由一系列偏置电流定义的不同工作点得到的。由于AMB具有不稳定开环特性,因此采用位置比例积分导数(PID)控制器来稳定被控对象。用持续扰动电流激励系统,收集实验数据。用确定的参数调整后的模型能够以更高的精度描述植物动态。通过有效地改变偏置电流,可以在基于模型的控制方法中利用识别的参数集。
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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