@inproceedings{63e9a8b24d7e42d8b2b163bbd3074b12,
title = "Fault tolerant control strategy based on model predictive control and unscented Kalman filter for permanent magnet synchronous motor",
abstract = "Permanent Magnet Synchronous Motors (PMSMs) are now extensively used in many critical applications. There is an increasing need for the motor and control system to have fault tolerant capabilities. This paper presents a fault tolerant control strategy to operate the PMSM during inter-turn fault conditions. The proposed technique combines the Model Predictive Control (MPC) for the speed and current control loops, and an almost error-free Unscented Kalman Filter (UKF) to estimate the PMSM inter-turn fault ratio. The PMSM state-space model for healthy and faulty conditions will be presented. Also, the equations and the remedial action of the MPC and UKF are provided in detail. The proposed algorithm is applied to PMSM model as a case study with a range of simulation analysis and discussion of results.",
keywords = "Model predictive control, PMSM, fault diagnosis, fault tolerant, unscented Kalman filter",
author = "Ahmed Aboelhassan and {El Sayed}, Waseem and Ahmed Hebala and Michael Galea and Serhiy Bozhko",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021 ; Conference date: 01-08-2021 Through 04-08-2021",
year = "2021",
month = aug,
day = "1",
doi = "10.1109/ICIEA51954.2021.9516257",
language = "English",
series = "Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "153--159",
booktitle = "Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021",
address = "United States",
}