An Improved Predictive Controller for PMSM based on Dual-Channel Feedback

Author:

Lu Junhao

Abstract

Abstract High-performance and high-power-density DC servo drives of permanent magnet synchronous motors (PMSM) are applied to the military, especially in airborne optoelectronic pods, light mines, and launch turntables in the aerospace field. The above application scenarios require the volume of drivers to be smaller and have large power outputs. In the field of pods and light mines, high bandwidth and good tracking performance are required, especially in terms of steady-state accuracy. Since light mines are used for target tracking scanning, the errors at the end of the optical rotating mechanism are amplified tens or even hundreds of times after transmission through the line of sight to the target end. Therefore, the requirements for steady-state accuracy are extremely high. In this article, a predictive control method is proposed, using a sliding mode variable structure controller to make up for the error arising from system parameter changes in predictive control. Finally, a dual-channel rotary transformer feedback position coarse-fine combination algorithm method is studied to reduce the angular measurement error and further improve steady-state accuracy.

Publisher

IOP Publishing

Reference16 articles.

1. Torque Ripple Reduction of DTC Based on an Analytical Model of PMSM;Zhong;World Electric Vehicle Journal,2020

2. Control Algorithm of Permanent Magnet Direct Drive Belt Conveyor System for Mining Based on Reduced Order Model;Liu;International journal of pattern recognition and artificial intelligence,2021

3. Modeling and Simulation of Nine-Phase Permanent Magnet Synchronous Motor;Zhang;Energy and Power Engineering,2020

4. A discrete-time nonlinear robust controller for current regulation in PMSM drives;Türker;Journal of Electrical Engineering & Technology,2017

5. Current steady error elimination algorithm for permanent magnet synchronous motor dead-beat current control;Xie;Electric Machines & Control Application,2018

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