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Dual-Rate Extended Kalman Filter Based Path-Following Motion Control for an Unmanned Ground Vehicle: Realistic Simulation

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Dual-Rate Extended Kalman Filter Based Path-Following Motion Control for an Unmanned Ground Vehicle: Realistic Simulation

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dc.contributor.author Carbonell-Lázaro, Rafael es_ES
dc.contributor.author Cuenca, Ángel es_ES
dc.contributor.author Casanova Calvo, Vicente es_ES
dc.contributor.author Pizá, Ricardo es_ES
dc.contributor.author Salt Llobregat, Julián José es_ES
dc.date.accessioned 2022-10-07T18:06:51Z
dc.date.available 2022-10-07T18:06:51Z
dc.date.issued 2021-11-13 es_ES
dc.identifier.uri http://hdl.handle.net/10251/187286
dc.description.abstract [EN] In this paper, a two-wheel drive unmanned ground vehicle (UGV) path-following motion control is proposed. The UGV is equipped with encoders to sense angular velocities and a beacon system which provides position and orientation data. Whereas velocities can be sampled at a fast rate, position and orientation can only be sensed at a slower rate. Designing a dynamic controller at this slower rate implies not reaching the desired control requirements, and hence, the UGV is not able to follow the predefined path. The use of dual-rate extended Kalman filtering techniques enables the estimation of the fast-rate non-available position and orientation measurements. As a result, a fast-rate dynamic controller can be designed, which is provided with the fast-rate estimates to generate the control signal. The fast-rate controller is able to achieve a satisfactory path following, outperforming the slow-rate counterpart. Additionally, the dual-rate extended Kalman filter (DREKF) is fit for dealing with non-linear dynamics of the vehicle and possible Gaussian-like modeling and measurement uncertainties. A Simscape Multibody (TM) (Matlab(R)/Simulink) model has been developed for a realistic simulation, considering the contact forces between the wheels and the ground, not included in the kinematic and dynamic UGV representation. Non-linear behavior of the motors and limited resolution of the encoders have also been included in the model for a more accurate simulation of the real vehicle. The simulation model has been experimentally validated from the real process. Simulation results reveal the benefits of the control solution. es_ES
dc.description.sponsorship Grant RTI2018-096590-B-I00 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF Away of making Europe" and Grant PRE2019-088467 funded by MCIN/AEI/10.13039/501100011033 and by "ESF Investing in your future". es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Sensors es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Unmanned ground vehicle es_ES
dc.subject Kalman filter es_ES
dc.subject Vehicle modeling and simulation es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.title Dual-Rate Extended Kalman Filter Based Path-Following Motion Control for an Unmanned Ground Vehicle: Realistic Simulation es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/s21227557 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096590-B-I00/ES/DISEÑO EFICIENTE DE SISTEMAS DE CONTROL EN RED INALAMBRICA APLICADOS A UXVS UTILIZANDO TECNICAS DE CONTROL CON MUESTREO NO CONVENCIONAL Y BASADAS EN EVENTOS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//PRE2019-088467//AYUDA PREDOCTORAL AEI-CARBONELL LAZARO. PROYECTO: DISEÑO EFICIENTE DE SISTEMAS DE CONTROL EN RED INALAMBRICA APLICADOS A UXVS UTILIZANDO TECNICAS DE CONTROL CON MUESTREO NO CONVENCIONAL Y BASADAS EN EVENTOS./ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Carbonell-Lázaro, R.; Cuenca, Á.; Casanova Calvo, V.; Pizá, R.; Salt Llobregat, JJ. (2021). Dual-Rate Extended Kalman Filter Based Path-Following Motion Control for an Unmanned Ground Vehicle: Realistic Simulation. Sensors. 21(22):1-17. https://doi.org/10.3390/s21227557 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/s21227557 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 17 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 21 es_ES
dc.description.issue 22 es_ES
dc.identifier.eissn 1424-8220 es_ES
dc.identifier.pmid 34833632 es_ES
dc.identifier.pmcid PMC8624498 es_ES
dc.relation.pasarela S\449976 es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
upv.costeAPC 1785,39 es_ES


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