A New Cascaded Adaptive Deadbeat Control Method for PMSM Drive

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Number of pages10
Journal / PublicationIEEE Transactions on Industrial Electronics
Online published1 Jun 2022
Publication statusOnline published - 1 Jun 2022

Abstract

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.

Research Area(s)

  • Adaptation models, Adaptive control, coefficient identification, deadbeat control, Load modeling, Mathematical models, permanent magnet synchronous motor (PMSM), Predictive models, Robustness, Synchronous motors, Torque