A New Cascaded Adaptive Deadbeat Control Method for PMSM Drive

Yong Chen, Chunhua Liu, Senyi Liu, Zaixin Song

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)


This paper proposes a novel cascaded adaptive deadbeat (CADB) control method for permanent magnet synchronous motor (PMSM) drives. Firstly, an adaptive deadbeat (DB)-based current controller is proposed with a simplified first-order current loop dynamic model. The motor parameters are compressed into few identifiable coefficients, and an improved gradient method with adjustable gain factor is employed to identify these time-varying coefficients. Therefore, there is no need to design an extra observer to obtain specific motor physical parameters. Next, on basis of differential equation solving method, a similar model of speed loop is presented and adopted for the design of an adaptive speed controller. A robust DB-based tracking control law and a feedback control law are applied in the proposed adaptive controller. The stability of proposed adaptive controller is confirmed by using the Lyapunov theorem. Finally, the proposed CADB control system is experimentally carried out in steady state and transient state. The test results indicate that the system has the good dynamic performance and robustness to the disturbance of parameters and loads.

Original languageEnglish
Pages (from-to)1
Number of pages1
JournalIEEE Transactions on Industrial Electronics
Publication statusAccepted/In press - 2022
Externally publishedYes


  • Adaptive control
  • coefficient identification
  • deadbeat control
  • permanent magnet synchronous motor (PMSM)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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