Novel Deadbeat Predictive Current Control for PMSM With Parameter Updating Scheme

Abstract

Deadbeat predictive current control (DPCC) has been employed for permanent magnet synchronous machines (PMSMs) due to its satisfactory steady-state and dynamic performances. However, dependence on the accuracy of parameters is a major barrier for its widespread application. To address this problem, a novel control method that can update related items with internal parameters online, in which winding resistance, flux linkage, and stator inductance are considered simultaneously, is proposed in this article. First, the current prediction errors in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> -axis and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> -axis are analyzed and stored. It has to be mentioned that the extended Kalman filter (EKF) is applied to filter the measured current and optimize the estimated current. Second, through the error of two consecutive control periods, the related items can update in real time. Finally, an updating mechanism based on DPCC is established to control the drive system. Since only measured current is used in the control system, the proposed algorithm is easy to implement. The simulation and experimental results indicate the effectiveness of the proposed method under complex parameters mismatch conditions.