High-Precision Position Control of a Linear-Switched Reluctance Motor Using a Self-Tuning Regulator

High-Precision Position Control of a Linear-Switched Reluctance Motor Using a Self-Tuning Regulator
复制标题

DOI:
10.1109/tpel.2010.2051685
复制
发表时间:
2010-06
影响因子:
6.7
通讯作者:
S. Zhao;Norbert C. Cheung;W. Gan;Jinming Yang
S. Zhao;Norbert C. Cheung;W. Gan;Jinming Yang
中科院分区:
工程技术1区
文献类型:
--
作者:
S. Zhao;Norbert C. Cheung;W. Gan;Jinming Yang

文献摘要

被引文献

相似文献

线性开关磁阻电机(LSRM)的高精度位置控制在运动控制领域具有重要意义。由于LSRM固有的非线性和系统的不确定性,基于静态模型的控制器有时不能给出令人满意的输出性能。本文提出了一种基于极点放置算法的自调谐调节器(STR),用于LSRM的高精度位置跟踪。通过对LSRM位置跟踪系统的时间尺度特征分析和力特征研究,将位置跟踪模型视为一个二阶系统。与基于静态模型的控制方案不同,LSRM的动态模型可以通过在线估计得到。此外,还考虑了一些实际的方面。由于未建模的动力学和高频测量噪声,在实际控制信号中存在一定的振荡,通过适当设计滤波器可以减小这些振荡。仿真和实验结果都表明,在所提出的STR控制下,位置跟踪系统能够在恶劣环境下以期望的性能再现参考信号。结果表明,该方法对LSRM高精度位置跟踪具有较好的鲁棒性。
High-precision position control of linear-switched reluctance motor (LSRM) is important in motion-control industry. The static model-based controller sometimes cannot give satisfactory output performance due to the inherent nonlinearities of LSRM and the uncertainties of the system. In this paper, a self-tuning regulator (STR) based on the pole-placement algorithm is proposed for high-precision position tracking of the LSRM. Following the time-scale characteristics analysis of LSRM position-tracking system and force-characteristic investigation, the position-tracking model is treated as a second-order system. Different from the static model-based control schemes, the dynamic model of the LSRM can be obtained by online estimation. Also, some practical aspects are taken into account. Owing to the unmodeled dynamics and high-frequency measurement noises, there are some oscillations in the practical control signals, and they can be reduced by a properly designed filter. Both the simulation and experimental results demonstrate that, in the control of the proposed STR, the position-tracking system can reproduce the reference signal with the desired performance in harsh ambient. These results confirm that the method is effective and robust in the high-precision position tracking of LSRM.