Neuro-fuzzy control of interior permanent magnet synchronous motors: Stability analysis and implementation

Dong Quang Dang, Nga Thi Thuy Vu, Han Ho Choi, Jin Woo Jung

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

This paper investigates a robust neuro-fuzzy control (NFC) method which can accurately follow the speed reference of an interior permanent magnet synchronous motor (IPMSM) in the existence of nonlinearities and system uncertainties. A neuro-fuzzy control term is proposed to estimate these nonlinear and uncertain factors, therefore, this difficulty is completely solved. To make the global stability analysis simple and systematic, the time derivative of the quadratic Lyapunov function is selected as the cost function to be minimized. Moreover, the design procedure of the online self-tuning algorithm is comparatively simplified to reduce a computational burden of the NFC. Next, a rotor angular acceleration is obtained through the disturbance observer. The proposed observer-based NFC strategy can achieve better control performance (i.e., less steady-state error, less sensitivity) than the feedback linearization control method even when there exist some uncertainties in the electrical and mechanical parameters. Finally, the validity of the proposed neuro-fuzzy speed controller is confirmed through simulation and experimental studies on a prototype IPMSM drive system with a TMS320F28335 DSP.

Original languageEnglish
Pages (from-to)1439-1450
Number of pages12
JournalJournal of Electrical Engineering and Technology
Volume8
Issue number6
DOIs
StatePublished - Nov 2013

Keywords

  • Interior permanent magnet synchronous motor (IPMSM)
  • Linear matrix inequality (LMI)
  • Neuro-fuzzy control (NFC)
  • Robustness
  • Speed control
  • System uncertainties

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