Abstract
The cubature Kalman filter (CKF) is the closest approximation known so far to the Bayesian filter that could be designed in a nonlinear setting under the Gaussian assumption. Unlike the extended Kalman filter (EKF), CKF does not require evaluation of Jacobians during the estimation process, while in EKF the nonlinear functions are approximated by their Jacobians, the first-order Taylor’s series approximation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The continuous state-space model, \(\dot{\mathbf{x }}=A\mathbf x +B\mathbf u \), can be discretised by using Euler’s method as
$$\mathbf x _{n+1}=(\mathbf I _n+A\varDelta t)\mathbf x _n+\varDelta t B \mathbf u ,$$where \(\varDelta t\) is the sampling time and \(\mathbf I _n\) is the \(n^{th}\) order identity matrix
References
Arasaratnam I, Haykin S (2009) Cubature kalman filters. IEEE Trans Autom Control 54(6):1254–1269
DS1103 PPC Controller Board catalogue, Paderborn, Germany, 2008, howpublished = https://www.dspace.com/en/inc/home/products/hw/singbord/ppcconbo.cfm. Accessed 10 Feb 2018
Kim T, Lee H, Ehsani M (2007) Position sensorless brushless dc motor/generator drives: review and future trends. IET Electr Power Appl 1(4):557–564
Krishnan R (2017) Permanent magnet synchronous and brushless DC motor drives. CRC press, Boca Raton
Lee B-K, Ehsani M (2003) Advanced simulation model for brushless dc motor drives. Electr Power Compon Syst 31(9):841–868
MITSUBISHI Intelligent power modules catologue, 1998, howpublished = http://www.mitsubishielectric.com/semiconductors/files/manuals/powermos6_0.pdf. Accessed 10 Feb 2018
Potnuru D, Chandra KPB, Arasaratnam I, Gu D-W, Mary KA, Ch SB (2016) Derivative-free square-root cubature kalman filter for non-linear brushless dc motors. IET Electr Power Appl 10(5):419–429
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Chandra, K.P.B., Gu, DW. (2019). Cubature Kalman Filter. In: Nonlinear Filtering. Springer, Cham. https://doi.org/10.1007/978-3-030-01797-2_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-01797-2_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01796-5
Online ISBN: 978-3-030-01797-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)