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

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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.

Original languageEnglish
Title of host publicationAdvances in Dynamics of Vehicles on Roads and Tracks - Proceedings of the 26th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2019
EditorsMatthijs Klomp, Fredrik Bruzelius, Jens Nielsen, Angela Hillemyr
PublisherSpringer Science and Business Media Deutschland GmbH
Pages1616-1623
Number of pages8
ISBN (Print)9783030380762
DOIs
StatePublished - 2020
Event26th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2019 - Gothenburg, Sweden
Duration: 12 Aug 201916 Aug 2019

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364

Conference

Conference26th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2019
Country/TerritorySweden
CityGothenburg
Period12/08/1916/08/19

Keywords

  • Active roll control
  • Dual extended Kalman filters
  • Recursive least square
  • State and parameter estimation

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