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dc.creatorPyrhönen, Lauries
dc.creatorJaiswal, Surajes
dc.creatorGarcía-Agúndez Blanco, Alfonsoes
dc.creatorGarcía Vallejo, Danieles
dc.creatorMikkola, Aki
dc.identifier.citationPyrhönen, L., Jaiswal, S., García-Agúndez, A., García Vallejo, D. y Mikkola, A.M. (2023). Linearization-based state-transition model for the discrete extended Kalman filter applied to multibody simulations. Multibody System Dynamics, 57 (1), 55-72.
dc.descriptionThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit
dc.description.abstractThis study investigates the discrete extended Kalman filter as applied to multibody systems and focuses on accurate formulation of the state-transition model in the framework. The proposed state-transition model is based on the coordinate-partitioning method and linearization of the multibody equations of motion. The approach utilizes the synergies between the integration of states and estimator covariances without overly simplifying the integrator structure. The proposed method is analyzed with a forward dynamics analysis of a four-bar mechanism. The results show that the stability of the state-transition model in the forward dynamics analysis is significantly enhanced with the proposed method compared with the forward Euler-based methods. The computational efficiency of the novel method was significantly lower in comparison to forward Euler-based methods, which was found to be mainly due to the computation of the Jacobian matrix of the nonlinear state equation. However, the increase in computational cost can be considered acceptable in Kalman-filtering applications, where the exact Jacobian of the state equation is
dc.relation.ispartofMultibody System Dynamics, 57 (1), 55-72.
dc.rightsAtribución 4.0 Internacional*
dc.subjectDiscrete extended Kalman filteres
dc.subjectRigid multibody systemses
dc.subjectLinearized dynamicses
dc.subjectExponential integrationes
dc.titleLinearization-based state-transition model for the discrete extended Kalman filter applied to multibody simulationses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería Mecánica y de Fabricaciónes
dc.contributor.groupUniversidad de Sevilla. TEP111: Ingeniería Mecánicaes
dc.journaltitleMultibody System Dynamicses
dc.contributor.funderBusiness Finlandes

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Atribución 4.0 Internacional
Except where otherwise noted, this item's license is described as: Atribución 4.0 Internacional