Speed Control of Load Torque Feedforward Compensation Based on Linear Active Disturbance Rejection for Five-Phase PMSM

Zhi Kuang, Bochao Du, Shumei Cui, C. C. Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

46 Citations (Scopus)

Abstract

This study focuses on the speed control problem of a five-phase permanent magnet synchronous motor (PMSM) in the presence of a variable load torque and unknown model parameters. To overcome the mutual transmission of motor torque ripple and load disturbance when the five-phase PMSM directly drives the load, a control method of load torque feedforward compensation based on linear auto disturbance rejection controller (LADRC) is proposed. First, the load torque observer is introduced to observe the load torque which is used as feedforward compensation to eliminate the effects of load torque changes. Second, an LADRC in the outer speed loop is presented to estimate the disturbance, and the stability of LADRC is analyzed. Third, the proposed torque feedforward method based on the LADRC is compared with the traditional proportional integral (PI) torque feedforward method. The PI regulators for current loops are designed. Finally, the simulation models are built and the control algorithms are both implemented using a TMS320F28335 DSP. The simulation and experiment results show that the proposed load torque feedforward compensation based on the LADRC produces excellent dynamic performance, such as smaller overshoot and faster response time. The proposed control scheme is robust and has a strong anti-disturbance ability, even in the case of large load torque disturbances.

Original languageEnglish
Article number8886430
Pages (from-to)159787-159796
Number of pages10
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 2019
Externally publishedYes

Keywords

  • Five phase PMSM
  • linear active disturbance rejection controller (LADRC)
  • linear extended state observe (LESO)
  • load torque observer

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering

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