Active Disturbance-Rejection-Based Speed Control in Model Predictive Control for Induction Machines

• Published in: IEEE transactions on industrial electronics (1982) Vol. 67; no. 4; pp. 2574 - 2584
• Main Authors: Yan, Liming, Wang, Fengxiang, Dou, Manfeng, Zhang, Zhenbin, Kennel, Ralph, Rodriguez, Jose
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Active control; Dynamic response; Economic models; Electromagnetic induction; Electromagnetics; Error analysis; Error compensation; Induction machine; Induction machines; Induction motors; Mathematical model; Mathematical models; model predictive control (MPC); nonlinear prediction error; Optimal control; Parameters; Predictive control; Proportional integral; Rejection; Speed control; Stators; Torque; Torque control; Tracking errors
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2019.2912785

Finite set model predictive torque control (FCSMPTC) of induction machines has received widespread attention in recent years due to its fast dynamic response, intuitive concept, and ability to handle nonlinear constraints. However, FCSMPTC essentially belongs to the open-loop control paradigm, and unmatched parameters inevitably cause electromagnetic torque tracking error. In addition, the outer loop (i.e., the speed loop) based on a proportional-integral (PI) regulator cannot achieve optimal control between speed dynamic response and torque tracking error compensation. The traditional control paradigm is abbreviated as PI-MPTC. In order to solve the aforementioned problem, this paper proposes active disturbance-rejection-based model predictive torque control (ADR-MPTC). First, the influence mechanism of mismatched parameters on torque prediction error in PI-MPTC is studied, and then the performance of a traditional PI regulator used to compensate for torque prediction error is analyzed. Second, this paper introduces several parts of the proposed ADR-MPTC, including the design of the torque prediction error observer, nonlinear prediction error compensation strategies, an enhanced predictive torque control, and a simplified full-order flux observer. Finally, PI-MPTC and ADR-MPTC are studied experimentally. The experimental results show that compared with PI-MPTC, ADR-MPTC performs better in dynamic and steady states, and has stronger robustness.