Voltage Control of IPMSM Servo Drive in Constant Power Region With Intelligent Parameter Estimation

Faa Jeng Lin, Chih Wei Liu, Po Lun Wang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

A novel voltage control scheme for an interior permanent magnet synchronous motor (IPMSM) servo drive in the constant power region with intelligent estimation of the motor parameter is proposed in this study. In the novel voltage control scheme, a feedforward voltage angle controller is proposed where an intelligent parameter estimation method by using a wavelet fuzzy neural network (WFNN) is developed to estimate the $q$ -axis inductance online. In this study, in order to minimize the copper loss, a flux-weakening (FW) control scheme under maximum phase voltage is developed first. Then, an adaptive backstepping based nonlinear controller (ABNC) considering nonzero $d$ -axis current is developed to improve the robustness of the speed control. The Lyapunov stability theorem is used to derive the adaptive law of the online estimation of the lumped uncertainty to ensure the asymptotical stability of the ABNC. Moreover, a feedforward voltage angle controller is developed for the voltage control where the $q$ -axis current controller is retained in order to ensure the steady-state performance of the control system. Furthermore, the WFNN is adopted to estimate the actual $q$ -axis inductance value online for the feedforward voltage angle controller to improve the dynamic response. In addition, some experimental results are demonstrated to verify the effectiveness of the proposed voltage control scheme with ABNC in the constant power region.

Original languageEnglish
Pages (from-to)99243-99256
Number of pages14
JournalIEEE Access
Volume10
DOIs
StatePublished - 2022

Keywords

  • Interior permanent magnet synchronous motor (IPMSM)
  • adaptive backstepping based nonlinear controller (ABNC)
  • flux-weakening (FW) control
  • maximum torque per ampere (MTPA) control
  • online parameter estimation
  • wavelet fuzzy neural network (WFNN)

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