Intelligent Maximum Power Factor Searching Control Using Recurrent Chebyshev Fuzzy Neural Network Current Angle Controller for SynRM Drive System

Shih Gang Chen, Faa Jeng Lin, Chia Hui Liang, Chen Hao Liao

研究成果: 雜誌貢獻期刊論文同行評審

31 引文 斯高帕斯(Scopus)

摘要

To develop a high-performance synchronous reluctance motor (SynRM) drive system, a novel maximum power factor control (MPFC) using a current angle controller with stator resistance and stator flux estimators is proposed. First, a traditional maximum power factor control system using a saliency ratio of the SynRM to generate a fixed current angle command is described. Since the saliency ratio requires offline prepreparation and cannot be adjusted automatically, it is difficult to improve the performance of the MPFC in different operating regions because of the increasing of manufacturing cost and time-consumption. Therefore, an intelligent-maximum power factor searching control (MPFSC) using a recurrent Chebyshev fuzzy neural network (RCFNN) current angle controller is developed for the speed control of a SynRM. In order to search the online optimal power factor (PF) points of the SynRM under different operating conditions, the RCFNN current angle controller is designed to produce the compensated current angle command. Moreover, a proportional-integral speed controller is adopted to generate the stator current magnitude command, and the proposed intelligent-MPFSC is employed to generate the current angle command. Furthermore, the proposed intelligent-MPFSC system is implemented in a 32-bit floating-point TMS320F28075 digital signal processor. Finally, from the experimental results, the current angle commands of the optimal PF can be effectively obtained online at different speed operating commands with varied load torque.

原文???core.languages.en_GB???
文章編號9167461
頁(從 - 到)3496-3511
頁數16
期刊IEEE Transactions on Power Electronics
36
發行號3
DOIs
出版狀態已出版 - 3月 2021

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