Model Predictive Control and Position Sensorless Control Algorithm for Induction Motor

• Published in: Journal of physics. Conference series Vol. 1993; no. 1; pp. 12016 - 12023
• Main Authors: Zhu, Keke, Ruan, Lin
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.08.2021
• Subjects: Adaptive algorithms; Adaptive control; Control algorithms; Control theory; Directional control; Enumeration; Induction motors; Model reference adaptive control; Position sensing; Predictive control; Robustness; Static characteristics; Tracking control
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1993/1/012016

Abstract In view of the traditional finite set model predictive control of induction motor, the enumeration method is used to select only one optimal voltage vector in one control cycle, which causes the deviation of stator current in the tracking control process, and a duty cycle model predictive current control algorithm is proposed. In this algorithm, duty cycle control is introduced on the basis of traditional model prediction algorithm. In a control period, an optimal non-zero vector and a zero vector act together, and the action time of the two is calculated. Based on the duty cycle model predictive control algorithm, the model reference adaptive speed estimation algorithm is introduced to improve the robustness of the model. Finally, the dynamic and static characteristics of vector control and two model predictive control algorithms are analyzed through simulation comparison, and the feasibility of the proposed speed estimation algorithm is verified on the basis of the duty ratio model predictive algorithm, and the robustness of the two estimation methods is compared. The superiority of the prediction algorithm of duty cycle model and the improved speed estimation algorithm is proved.