4.8 Article

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

期刊

IEEE TRANSACTIONS ON POWER ELECTRONICS
卷 36, 期 3, 页码 3496-3511

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPEL.2020.3016709

关键词

Reactive power; Fuzzy neural networks; Fuzzy control; Stators; Chebyshev approximation; Torque; Neural networks; Current angle controller; maximum power factor searching control (MPFSC); power factor (PF); recurrent Chebyshev fuzzy neural network (RCFNN); synchronous reluctance motor (SynRM)

资金

  1. Ministry of Science and Technology of Taiwan, R.O.C. [MOST 107-2221-E-008-078-MY3]

向作者/读者索取更多资源

A novel maximum power factor control system is proposed for a high-performance synchronous reluctance motor drive system, utilizing a current angle controller with stator resistance and stator flux estimators. By employing a recurrent Chebyshev fuzzy neural network current angle controller, online optimal power factor points of the SynRM can be effectively obtained under different operating conditions.
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.

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