Event-triggering H∞-based observer combined with NN for simultaneous estimation of vehicle sideslip and roll angles with network-induced delays

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dc.contributor.author López Boada, María Jesús
dc.contributor.author López Boada, Beatriz
dc.contributor.author Zhang, Hui
dc.date.accessioned 2021-03-23T11:17:55Z
dc.date.available 2021-03-23T11:17:55Z
dc.date.issued 2021-02
dc.identifier.bibliographicCitation Nonlinear dynamics, vol. 103, Feb. 2021, Pp. 2733-2752
dc.identifier.issn 0924-090X
dc.identifier.uri http://hdl.handle.net/10016/32207
dc.description.abstract Nowadays, vehicles are being fitted with systems that improve their maneuverability, stability, and comfort in order to reduce the number of accidents. Improving these aspects is of particular interest thanks to the incorporation of autonomous vehicles onto the roads. The knowledge of vehicle sideslip and roll angles, which are among the main causes of road accidents, is necessary for a proper design of a lateral stability and roll-over controller system. The problem is that these two variables cannot be measured directly through sensors installed in current series production vehicles due to their high costs. For this reason, their estimation is fundamental. In addition, there is a time delay in the relaying of information between the different vehicle systems, such as, sensors, actuators and controllers, among others. This paper presents the design of an H∞-based observer that simultaneously estimates both the sideslip angle and the roll angle of a vehicle for a networked control system, with networked transmission delay based on an event-triggered communication scheme combined with neural networks (NN). To deal with the vehicle nonlinearities, NN and linear-parameter-varying techniques are considered alongside uncertainties in parameters. Both simulation and experimental results are carried out to prove the performance of observer design.
dc.description.sponsorship This work was supported by the Agencia Estatal de Investigacion (AEI) of the Ministry of Science and Innovation of the Government of Spain through the project RTI2018-095143-B-C21.
dc.format.extent 20
dc.language.iso eng
dc.publisher Springer Nature Switzerland AG.
dc.rights © The Author(s) 2021
dc.rights This 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.
dc.rights Atribución 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by/3.0/es/
dc.subject.other Nonlinear vehicle dynamics
dc.subject.other Estimation
dc.subject.other Event-triggered
dc.subject.other Neural network
dc.subject.other LPV
dc.subject.other Model parameter uncertainty
dc.title Event-triggering H∞-based observer combined with NN for simultaneous estimation of vehicle sideslip and roll angles with network-induced delays
dc.title.alternative Event-triggering Hinfinity-based observer combined with NN for simultaneous estimation of vehicle sideslip and roll angles with network-induced delays
dc.type article
dc.subject.eciencia Ingeniería Mecánica
dc.identifier.doi https://doi.org/10.1007/s11071-021-06269-7
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. RTI2018-095143-B-C21
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 2733
dc.identifier.publicationlastpage 2752
dc.identifier.publicationtitle NONLINEAR DYNAMICS
dc.identifier.publicationvolume 103
dc.identifier.uxxi AR/0000027191
dc.contributor.funder Ministerio de Ciencia e Innovación (España)
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