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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Vydáno v:	Journal of engineering (Stevenage, England) Ročník 2019; číslo 17; s. 4304 - 4308
Hlavní autoři:	Gopinath, Gulur Raghavendra, Shyama, Prasad Das
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 01.06.2019 Wiley
Témata:	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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Popis
Shrnutí:	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