Abstract
This paper proposes an improved internal-model-control (IMC)-based proportional-integral (PI) current controller for a permanent magnet synchronous motor (PMSM) drive system to solve the parameter dependence problem. The parameter sensitivity of the conventional IMC-based PI controller is analyzed, which indicates that the parameters mismatch would cause oscillation or overshoot. Therefore, this paper utilizes an uncertainty and disturbance estimator to eliminate the impact of the parameters mismatch disturbance caused by the parameters variation. The proposed controller includes an IMC-based PI controller, which is responsible for tracking, and a disturbance estimator, which deals with other control difficulties. The performance and robustness are easily achieved by separately tuning the only two parameters (the desired closed-loop bandwidth and the estimator bandwidth). The frequency-domain characteristic of the proposed current controller indicates that it can effectively suppress the parameters mismatch disturbance. Simulations and experiments have verified the effectiveness of the proposed method.
Highlights
Thanks to the high reliability, high power factor, and high efficiency, permanent magnet synchronous motor (PMSM) has applied in important industrial applications [1]
Some current control strategies have played an essential role in the PMSM drive system, such as proportional-integral
According to (5), the IMC-based PI controller depends on PMSM model parameters including stator resistance and stator inductance
Summary
Thanks to the high reliability, high power factor, and high efficiency, permanent magnet synchronous motor (PMSM) has applied in important industrial applications [1]. The IMC-based PI current controller represents the proportional gain and integral gain of PI controller as an algebraic expression of both machine parameters and desired closed-loop bandwidth. Based on this conclusion, the parameters tuning is regarded as a single parameter (expected closed-loop bandwidth) optimization problem if the machine parameters are accurately known. The second method replaces PI controller with advanced control strategies such as model-free predictive control [13] and adaptive sliding mode control [14] These methods have improved the control performance in some aspects, faster transient-state response, or better robustness against machine parameter variations, but the superiority comes at the expense of higher current controller complexity. The part will analyze the parameter sensitivity of the IMC-based PI current controller
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