期刊
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 70, 期 4, 页码 3384-3393出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2022.3177808
关键词
Adaptive control; coefficient identification; deadbeat (DB) control; permanent magnet synchronous motor (PMSM)
In this article, a novel cascaded adaptive deadbeat (CADB) control method is proposed for permanent magnet synchronous motor drives. An adaptive deadbeat (DB) based current controller is first proposed with a simplified first-order current loop dynamic model. The motor parameters are compressed into few identifiable coefficients, and an improved gradient method is used to identify these time-varying coefficients. Then, a similar model of speed loop is presented and employed for the design of an adaptive speed controller. The stability of the proposed adaptive controller is confirmed by using the Lyapunov theorem. Finally, the proposed CADB control system is experimentally carried out to validate its performance.
In this article, we propose a novel cascaded adaptive deadbeat (CADB) control method for permanent magnet synchronous motor drives. First, 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 an 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 the basis of the 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 to the proposed adaptive controller. The stability of the proposed adaptive controller is confirmed by using the Lyapunov theorem. Finally, the proposed CADB control system is experimentally carried out in the steady state and transient state. The test results indicate that the system has good dynamic performance and robustness to the disturbance of parameters and loads.
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