Sensorless control of PMSM using an adaptively tuned SCKF

This study reports the application of an adaptively tuned square-root Cubature Kalman filter (SCKF) for the speed and position estimation of a permanent magnet synchronous motor (PMSM) drive. The proposed estimator is observed to exhibit improved noise rejection characteristics as compared to the hi...

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Veröffentlicht in:Journal of engineering (Stevenage, England) Jg. 2019; H. 17; S. 4304 - 4308
Hauptverfasser: Gopinath, Gulur Raghavendra, Shyama, Prasad Das
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 01.06.2019
Wiley
Schlagworte:
adaptively tuned SCKF
adaptively tuned square-root cubature Kalman filter
Bayes methods
CKF
control algorithms
data acquisition
general Bayesian estimation equation
improved noise rejection characteristics
invertors
Kalman filters
multivariate moment integrals
National Instruments data acquisition system
NI PCI-6221
nonlinear filter
nonlinear filters
numerical stability
permanent magnet motors
permanent magnet synchronous motor drive
PMSM
position estimation
sensorless control
sensorless machine control
speed estimation
square-root algorithm
synchronous motor drives
The 9th International Conference on Power Electronics, Machines and Drives (PEMD 2018)
third degree spherical-radial cubature rule
three-phase inverter-fed PMSM
sensorless control
NI PCI-6221
third degree spherical-radial cubature rule
square-root algorithm
numerical stability
invertors
National Instruments data acquisition system
multivariate moment integrals
data acquisition
adaptively tuned SCKF
three-phase inverter-fed PMSM
Kalman filters
adaptively tuned square-root cubature Kalman filter
CKF
sensorless machine control
nonlinear filter
permanent magnet synchronous motor drive
speed estimation
improved noise rejection characteristics
nonlinear filters
position estimation
control algorithms
PMSM
synchronous motor drives
Bayes methods
permanent magnet motors
general Bayesian estimation equation
ISSN:2051-3305, 2051-3305
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Beschreibung
Zusammenfassung:This study reports the application of an adaptively tuned square-root Cubature Kalman filter (SCKF) for the speed and position estimation of a permanent magnet synchronous motor (PMSM) drive. The proposed estimator is observed to exhibit improved noise rejection characteristics as compared to the hitherto widely applied extended Kalman filter (EKF) observer. A third degree spherical–radial cubature rule is used in the Cubature Kalman filter (CKF) to numerically compute the multivariate moment integrals of the general Bayesian estimation equation. CKF is a non-linear filter which avoids linearisation and the associated errors. The realisation of CKF using the square-root algorithm results in numerical stability, as with the realisation of EKF using the square-root algorithm. Simulation results are presented for a three-phase inverter-fed PMSM, along with the experimental results. The estimator and the control algorithms are realised on the MATLAB real-time environment, interfaced with the hardware using the National Instruments data acquisition system NI PCI-6221.
ISSN:2051-3305
2051-3305
DOI:10.1049/joe.2018.8081