Investigating Electrical Drive Performance Employing Model Predictive Control and Active Disturbance Rejection Control Algorithms

Aboelhassan, Ahmed; Diab, Ahmed M.; Galea, Michael; Bozhko, Serhiy

Abstract

© 2020 The Institute of Electrical Engineers of Japan. Many issues can degrade the electrical drive performance such as cross-coupling, time delay, external disturbances, and parameter variation. The Synchronous Reference Frame (SRF) PI Current Controller (CC) is the most popular control scheme for the motor drive current control due to its simplicity. However, the PI controller does not have an optimal dynamic response due to the reasonably low transient response of the integral parts. Furthermore, the tuning of the PI controller depends heavily on the machine's parameters. Recently, alternative control schemes such as Model Predictive Control (MPC) and Active Disturbance Rejection Control (ADRC) are studied due to their dynamic performance and disturbance rejection capability, respectively. This paper presents a comparative study between the conventional PI, ADRC, and MPC control schemes applied for Permanent Magnet Synchronous Motor (PMSM) taking into consideration the operational issues of electrical drives.

Citation

Aboelhassan, A., Diab, A. M., Galea, M., & Bozhko, S. (2020, November). Investigating Electrical Drive Performance Employing Model Predictive Control and Active Disturbance Rejection Control Algorithms. Presented at 23rd International Conference on Electrical Machines and Systems, ICEMS 2020, Hamamatsu, Japan

• Presentation Conference Type: Edited Proceedings
• Conference Name: 23rd International Conference on Electrical Machines and Systems, ICEMS 2020
• Start Date: Nov 24, 2020
• End Date: Nov 27, 2020
• Acceptance Date: Jun 3, 2020
• Online Publication Date: Dec 22, 2020
• Publication Date: Dec 22, 2020
• Deposit Date: Mar 5, 2021
• Publicly Available Date: Mar 5, 2021
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 1379-1384
• Series Title: International Conference on Electrical Machines and Systems (ICEMS)
• Series ISSN: 2640-7841
• Book Title: 2020 23rd International Conference on Electrical Machines and Systems (ICEMS)
• ISBN: 9781728189307
• DOI: https://doi.org/10.23919/ICEMS50442.2020.9291218
• Public URL: https://nottingham-repository.worktribe.com/output/5367865
• Publisher URL: https://ieeexplore.ieee.org/document/9291218
• Additional Information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.