Simon Göltz, Daniel L. Ossig, Weixin Fu, O. Sawodny
{"title":"Nonlinear Flatness-Based Observer for Vehicle Dynamics Control","authors":"Simon Göltz, Daniel L. Ossig, Weixin Fu, O. Sawodny","doi":"10.1109/IECON48115.2021.9589831","DOIUrl":null,"url":null,"abstract":"This paper describes a novel nonlinear flatness-based state observer for vehicle dynamics control. The differential flatness property of a nonlinear vehicle model is used to derive a state observer for the lateral dynamics of a vehicle. Furthermore, a second state observer for the combined lateral and longitudinal movement is presented. Additionally, the flat outputs and the state transformations to bring both models into observability normal form are shown and the observer equations are derived. For this purpose, it is shown that the description of the vehicle model in suitable coordinates is necessary. The observers are applied to measurement data of a passenger car. The results show very good estimation results in convergence and tracking. The approach enables linear state estimation for a nonlinear vehicle model with a camera based ground sensor.","PeriodicalId":443337,"journal":{"name":"IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society","volume":"618 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON48115.2021.9589831","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper describes a novel nonlinear flatness-based state observer for vehicle dynamics control. The differential flatness property of a nonlinear vehicle model is used to derive a state observer for the lateral dynamics of a vehicle. Furthermore, a second state observer for the combined lateral and longitudinal movement is presented. Additionally, the flat outputs and the state transformations to bring both models into observability normal form are shown and the observer equations are derived. For this purpose, it is shown that the description of the vehicle model in suitable coordinates is necessary. The observers are applied to measurement data of a passenger car. The results show very good estimation results in convergence and tracking. The approach enables linear state estimation for a nonlinear vehicle model with a camera based ground sensor.