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Weighting Factor Selection Techniques for Predictive Torque Control of Induction Motor Drives: A Comparison Study

For the last few years, predictive torque control (PTC) has attracted the attention of the researchers due to its simplicity and effectiveness. In PTC, flux-weighting factor needs to be wisely adjusted since it affects greatly the performance of the drive system. Many research trials were devoted to...

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Bibliographic Details
Published in:Arabian journal for science and engineering (2011) 2018-02, Vol.43 (2), p.433-445
Main Authors: Mamdouh, M., Abido, M. A., Hamouz, Z.
Format: Article
Language:English
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Summary:For the last few years, predictive torque control (PTC) has attracted the attention of the researchers due to its simplicity and effectiveness. In PTC, flux-weighting factor needs to be wisely adjusted since it affects greatly the performance of the drive system. Many research trials were devoted to select this weighting factor or even eliminate it. Each of these trials illustrates a method to overcome this problem and presents a solution to the conventional weighting factor calculation method. This paper presents a critical evaluation of the performance of recently proposed methods for weighting factor selection for finite control set PTC. Based on the way the weighting factor is calculated, the methods are classified to offline and online methods. In this study, more focus will be directed to the evaluation of the online methods since they can update the weighting factor automatically if the operating point changes. Specifically, four recently developed methods along with the conventional method are considered in this study. Flux ripple, torque ripple, current total harmonic distortion, and average switching frequency are adopted as the judging criteria for this comparison. Simulations at different operating points are used to assess the performance of each method, and the characteristics of each method are compared according to the performance indices suggested. The strengths and weaknesses of each method are highlighted. Therefore, the suitable method can be identified according to different application requirements.
ISSN:2193-567X
1319-8025
2191-4281
DOI:10.1007/s13369-017-2842-2