LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Analysis of Current Predictive Control Algorithm for Permanent Magnet Synchronous Motor Based on Three-Level Inverters

Photo by charlesdeluvio from unsplash

In some high-precision control applications, such as defense industry and computerized numerical control machine tools, fast and stable electromagnetic torque response is required to ensure the high dynamic performance of… Click to show full abstract

In some high-precision control applications, such as defense industry and computerized numerical control machine tools, fast and stable electromagnetic torque response is required to ensure the high dynamic performance of the system, while traditional PI control often cannot meet its requirements. For this purpose, a predictive control algorithm based on the deadbeat control algorithm is proposed in order to improve the performance of the motor current loop. In order to solve the problem that the conventional deadbeat control algorithm has a large dependence on system parameters and low robustness, this paper proposes an improved deadbeat control scheme for the permanent magnet synchronous motor based on the three-level inverters. The scheme is based on the second theorem of Lyapunov stability. The improved deadbeat control algorithm can achieve a good output waveform when the switching frequency is not high and the response speed is fast. The robustness of the system is improved, and there are good characteristics in reduced torque ripple. Compared to the traditional PI regulators, the improved deadbeat control can quickly track the current commands without overshoot and oscillation and suppress torque ripple. The simulation and experimental results show that the improved deadbeat control proposed in this paper has good dynamic and static performance.

Keywords: control; predictive control; deadbeat control; motor; control algorithm

Journal Title: IEEE Access
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.