Sensorless Control of IPMSM Based on Regression Model

被引:51
作者
Choi, Jongwon [1 ]
Nam, Kwanghee [1 ]
Bobtsov, Alexey A. [2 ]
Ortega, Romeo [3 ]
机构
[1] Pohang Univ Sci & Technol, Dept Elect Engn, Pohang 790784, South Korea
[2] ITMO Univ, Dept Control Syst & Informat, St Petersburg 197101, Russia
[3] CNRS, SUPELEC, Lab Signaux & Syst, F-91192 Gif Sur Yvette, France
关键词
Gradient algorithm; interior permanent-magnet synchronous motor (IPMSM); linear regression form; nonlinear observer; persistency of excitation; saliency; sensorless control signal injection; EXTENDED KALMAN FILTER; SYNCHRONOUS MOTOR; SPEED CONTROL; POSITION; OBSERVER; PARAMETERS;
D O I
10.1109/TPEL.2018.2883303
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A position-sensorless algorithm is developed for an interior permanent-magnet synchronous motor, while reflecting the saliency in an extended electromotive force term. Active flux is converted into a new linear regression form, and a high-pass filter was applied. Then, the gradient algorithm is applied to derive an estimate of the active flux in the stationary frame. The proposed observer is an inherently sensorless type because it does not require the rotor speed or position information. It is practically attractive since it does not require the use of pure integrator that is marginally stable. In addition, the observer can be constructed without the phase modulation flux linkage constant. It is basically a model-based method. However, it is easily extended to a signal injection method that is robust in the low-speed region. Ultimate boundedness is established using the persistency of excitation condition. Validity of the algorithm is demonstrated experimentally via torque and speed control with a full load in the low-speed range.
引用
收藏
页码:9191 / 9201
页数:11
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