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- Title
Sensorless Inverter-Fed Compressor Drive System Using Back- EMF Estimator with PIDNN Torque Observer.
- Authors
Lin, Faa‐Jeng; Hung, Ying‐Chih; Chen, Jia‐Ming; Kao, Zi‐Yin
- Abstract
A saliency back- EMF estimator with a proportional-integral-derivative neural network ( PIDNN) torque observer is proposed in this study to improve the speed estimating performance of a sensorless interior permanent magnet synchronous motor ( IPMSM) drive system for an inverter-fed compressor. The PIDNN torque observer is proposed to replace the conventional proportional-integral-derivative ( PID) torque observer in a saliency back- EMF estimator to improve the estimating performance of the rotor flux angle and speed. The proposed sensorless control scheme use square-wave type voltage injection method as the start-up strategy to achieve sinusoidal starting. When the motor speed gradually increases to a preset speed, the sensorless drive will switch to the conventional saliency back- EMF estimator using the PID observer or the proposed saliency back- EMF estimator using the PIDNN observer for medium and high speed control. The theories of the proposed saliency back- EMF rotor flux angle and speed estimation method are introduced in detail. Moreover, the network structure, the online learning algorithms and the convergence analyses of the PIDNN are discussed. Furthermore, a DSP-based control system is developed to implement the sensorless inverter-fed compressor drive system. Finally, some experimental results are given to verify the feasibility of the proposed estimator.
- Subjects
FREE precession; TORQUEMETERS; HUMAN body; TORQUE; KINEMATICS; VARIGNON'S theorem
- Publication
Asian Journal of Control, 2014, Vol 16, Issue 4, p1042
- ISSN
1561-8625
- Publication type
Article
- DOI
10.1002/asjc.786