{"title":"Distributed Nonlinear Predictive Control for Unmanned Air-Ground Vehicles","authors":"Alessandra Elisa Sindi Morando , Alessandro Bozzi , Simone Graffione , Roberto Sacile , Enrico Zero","doi":"10.1016/j.ifacol.2024.10.139","DOIUrl":null,"url":null,"abstract":"<div><div>This paper addresses the formation path tracking for a heterogeneous system made up of a steering car and a quadcopter. System modelling is based on Nonlinear Model Predictive Control (NMPC), which is a proper solution when considering a heterogeneous feet as not only it deals with non-linearities of the dynamic model but it is also a way to generate trajectories that can be communicated to other agents. Moreover, an Extended Kalman Filter (EKF) is employed to estimate the non-measurable ground robot state variables. Two separate simulations in Simulink for each agent have been carried out leading to promising results in terms of tracking errors. Indeed, tests show that the proposed solution allows the two vehicles to follow the reference aligned with a deviation of a few centimeters.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"58 21","pages":"Pages 37-42"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IFAC-PapersOnLine","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405896324018949","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
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Abstract
This paper addresses the formation path tracking for a heterogeneous system made up of a steering car and a quadcopter. System modelling is based on Nonlinear Model Predictive Control (NMPC), which is a proper solution when considering a heterogeneous feet as not only it deals with non-linearities of the dynamic model but it is also a way to generate trajectories that can be communicated to other agents. Moreover, an Extended Kalman Filter (EKF) is employed to estimate the non-measurable ground robot state variables. Two separate simulations in Simulink for each agent have been carried out leading to promising results in terms of tracking errors. Indeed, tests show that the proposed solution allows the two vehicles to follow the reference aligned with a deviation of a few centimeters.
期刊介绍：
All papers from IFAC meetings are published, in partnership with Elsevier, the IFAC Publisher, in theIFAC-PapersOnLine proceedings series hosted at the ScienceDirect web service. This series includes papers previously published in the IFAC website.The main features of the IFAC-PapersOnLine series are: -Online archive including papers from IFAC Symposia, Congresses, Conferences, and most Workshops. -All papers accepted at the meeting are published in PDF format - searchable and citable. -All papers published on the web site can be cited using the IFAC PapersOnLine ISSN and the individual paper DOI (Digital Object Identifier). The site is Open Access in nature - no charge is made to individuals for reading or downloading. Copyright of all papers belongs to IFAC and must be referenced if derivative journal papers are produced from the conference papers. All papers published in IFAC-PapersOnLine have undergone a peer review selection process according to the IFAC rules.
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