Fault Tolerant Control Strategy Based on Model Predictive Control and Unscented Kalman Filter for Permanent Magnet Synchronous Motor

被引:4
作者
Aboelhassan, Ahmed [1 ]
El Sayed, Waseem [2 ]
Hebala, Ahmed [3 ]
Galea, Michael [1 ]
Bozhko, Serhiy [3 ]
机构
[1] Univ Nottingham, Key Lab More Elect Aircraft Technol Zhejiang Prov, Ningbo, Peoples R China
[2] Univ Twente, Elect Engn Math & Comp Sci EEMCS, Enschede, Netherlands
[3] Univ Nottingham, PEMC Grp, Nottingham, England
来源
PROCEEDINGS OF THE 2021 IEEE 16TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2021) | 2021年
关键词
fault tolerant; fault diagnosis; Model predictive control; unscented Kalman filter; PMSM; FCS-MPC; MACHINES; DRIVE; IPMSM; PMSM;
D O I
10.1109/ICIEA51954.2021.9516257
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:153 / 159
页数:7
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