Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/37113
Title: Derivative Free Square-root Cubature Kalman Filter for Nonlinear Brushless DC Motors
Authors: Potnuru, D.
Chandra, K. P. B.
Arasaratnam, I.
Gu, Da-Wei
Alice Mary, K.
Sai Babu, C.
First Published: 2016
Publisher: Institution of Engineering and Technology (IET)
Citation: IET Electric Power Applications
Abstract: This paper presents a nonlinear square-root estimation scheme for brushless DC (BLDC) motors. The cubature Kalman filter (CKF) is the main estimation tool for the presented approach. The CKF is a recently proposed estimator for highly nonlinear systems and its efficacy has been verified on several applications. The square-root version of the CKF is preferred over the conventional CKF for real-time applications. Despite of having several advantages over other nonlinear filters, the CKF has not yet been explored for state estimation of electric drives in the electric drives community. In this paper, we present a square-root CKF for the speed and rotor position estimation of a highly nonlinear and high fidelity BLDC motor, these estimated speed and rotor position are then fed back to control the speed of the BLDC motor. The efficacy of the presented approach for low and high reference speeds, and in the presence of parametric uncertainties, is demonstrated by real-time experiments.
DOI Link: TBA
ISSN: 1751-8660
eISSN: 1751-8679
Links: TBA
http://hdl.handle.net/2381/37113
Embargo on file until: 1-Jan-10000
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Creative Commons “Attribution Non-Commercial No Derivatives” licence CC BY-NC-ND, further details of which can be found via the following link: http://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections:Published Articles, Dept. of Engineering

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