Vehicle sideslip angle measurement based on sensor data fusion using an integrated ANFIS and an Unscented Kalman Filter algorithm

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dc.contributor.author López Boada, Beatriz
dc.contributor.author López Boada, María Jesús
dc.contributor.author Díaz López, Vicente
dc.date.accessioned 2017-04-05T11:53:02Z
dc.date.available 2017-11-30T23:00:05Z
dc.date.issued 2016-05-01
dc.identifier.bibliographicCitation B.L. Boada, M.J.L. Boada, V. Díaz. Vehicle sideslip angle measurement based on sensor data fusion using an integrated ANFIS and an Unscented Kalman Filter algorithm. Mechanical Systems and Signal Processing, 2016, 72-73. Pp. 832–845.
dc.identifier.issn 0888-3270
dc.identifier.uri http://hdl.handle.net/10016/24469
dc.description.abstract Most existing ESC (Electronic Stability Control) systems rely on the measurement of both yaw rate and sideslip angle. However, one of the main issues is that the sideslip angle cannot be measured directly because the sensors are too expensive. For this reason, sideslip angle estimation has been widely discussed in the relevant literature. The modeling of sideslip angle is complex due to the non-linear dynamics of the vehicle. In this paper, we propose a novel observer based on ANFIS, combined with Kalman Filters in order to estimate the sideslip angle, which in turn is used to control the vehicle dynamics and improve its behavior. For this reason, low-cost sensor measurements which are integrated into the actual vehicle and executed in real time have to be used. The ANFIS system estimates a "pseudo-sideslip angle" through parameters which are easily measured, using sensors equipped in actual vehicles (inertial sensors and steering wheel sensors); this value is introduced in UKF in order to filter noise and to minimize the variance of the estimation mean square error. The estimator has been validated by comparing the observed proposal with the values provided by the CARSIM model, which is a piece of experimentally validated software. The advantage of this estimation is the modeling of the non-linear dynamics of the vehicle, by means of signals which are directly measured from vehicle sensors. The results show the effectiveness of the proposed ANFIS+UKF-based sideslip angle estimator.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.rights © Elsevier 2016
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Vehicle dynamics
dc.subject.other Sideslip angle
dc.subject.other Estimation
dc.subject.other Unscented Kalman Filter
dc.subject.other Adaptive Neuro-Fuzzy Inference System
dc.title Vehicle sideslip angle measurement based on sensor data fusion using an integrated ANFIS and an Unscented Kalman Filter algorithm
dc.type article
dc.subject.eciencia Ingeniería Mecánica
dc.identifier.doi http://doi.org/10.1016/j.ymssp.2015.11.003
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TRA2013-48030-C2-1-R
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 832
dc.identifier.publicationlastpage 845
dc.identifier.publicationtitle Mechanical System and Signal Processing
dc.identifier.publicationvolume 72-73
dc.identifier.uxxi AR/0000019406
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