Adaptive Backstepping Control for Synchronous Reluctance Motor Based on Intelligent Current Angle Control

Faa Jeng Lin, Ming Shi Huang, Shih Gang Chen, Che Wei Hsu, Chia Hui Liang

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

The design and analysis of a novel current angle-based adaptive backstepping (ABS) speed control system for a synchronous reluctance motor (SynRM) drive system is presented in this article. First, a proportional-integral control system with field-oriented control is described. Owing to the unmodeled dynamics and magnetic saturation effects of the SynRM, currently, there is no predominant way to design the command of the d-axis current for the SynRM. Therefore, an ABS based on the current angle control (ABS-CAC) system is designed for the speed tracking of SynRM. The ABS speed tracking control is proposed to generate the stator current command, and a lookup table of the results of maximum torque per ampere (MTPA) analysis by using the finite element analysis method is proposed to provide the current angle commands. Moreover, to improve the transient dynamic response of SynRM under MTPA operating conditions, an intelligent speed transient control system using a recurrent Hermite fuzzy neural network is developed to generate the compensated current angle command. The proposed intelligent ABS-CAC is implemented in a 32-bit floating-point digital signal processor TMS320F28075. Finally, some experimental results are provided to demonstrate the robustness and effectiveness of the proposed control system.

Original languageEnglish
Article number8907428
Pages (from-to)7465-7479
Number of pages15
JournalIEEE Transactions on Power Electronics
Volume35
Issue number7
DOIs
StatePublished - Jul 2020

Keywords

  • Adaptive backstepping (ABS) control
  • current angle control (CAC)
  • recurrent hermite fuzzy neural network (RHFNN)
  • synchronous reluctance motor (SynRM)

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