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2020 | OriginalPaper | Chapter

Estimation of States and Parameters with Dual Extended Kalman Filters for Active Roll Control

Authors: Seongjin Yim, Jaewon Nah, Manbok Park

Published in: Advances in Dynamics of Vehicles on Roads and Tracks

Publisher: Springer International Publishing

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Abstract

This paper presents a method that designs dual extended Kalman filters (EKFs) for active roll control. There are two Kalman filters: state and parameter estimators. The roll angle of a vehicle is estimated by the state estimator with roll rate measurement. It has been well known that the recursive least square (RLS) or parameter estimation scheme can be represented with Kalman filter. Using the fact, the parameters of a vehicle model are estimated by the parameter estimator using the estimated roll angle. Simulation and experiments are done to validate the proposed dual EKFs for active roll control.
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Metadata
Title
Estimation of States and Parameters with Dual Extended Kalman Filters for Active Roll Control
Authors
Seongjin Yim
Jaewon Nah
Manbok Park
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-38077-9_184

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