Data-Driven Modeling and Control for Lane Keeping System of Automated Driving Vehicles: Koopman Operator Approach
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Jin Sung | - |
dc.contributor.author | Quan, Ying Shuai | - |
dc.contributor.author | Chung, Chung Choo | - |
dc.date.accessioned | 2023-02-21T06:03:19Z | - |
dc.date.available | 2023-02-21T06:03:19Z | - |
dc.date.created | 2023-02-08 | - |
dc.date.issued | 2022-11 | - |
dc.identifier.issn | 1598-7833 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/182394 | - |
dc.description.abstract | This paper proposes the data-driven modeling and control method with the Koopman operator for the lane-keeping system. The vehicle can be modeled as a linear motion model but has underlying complicated nonlinear behavior. Thus, there exists a need to model the full vehicle dynamics effectively. To this end, we use the Koopman operator to express the full vehicle nonlinear dynamics as a linear structure. However, it is not practical to use the Koopman operator directly because it lies in infinite-dimensional space. Hence, we apply the extended dynamic mode decomposition to approximate the Koopman operator as a finite-dimensional linear operator. We conduct a comparative study between the linear model-based optimal control and the Koopman operator-based optimal control. As a result, it is observed that the proposed method reduces the system state by 20% compared to the linear model-based controller. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEEE Computer Society | - |
dc.title | Data-Driven Modeling and Control for Lane Keeping System of Automated Driving Vehicles: Koopman Operator Approach | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Chung, Chung Choo | - |
dc.identifier.doi | 10.23919/ICCAS55662.2022.10003764 | - |
dc.identifier.scopusid | 2-s2.0-85146631667 | - |
dc.identifier.wosid | 000927498500167 | - |
dc.identifier.bibliographicCitation | International Conference on Control, Automation and Systems, v.2022-November, pp.1049 - 1055 | - |
dc.relation.isPartOf | International Conference on Control, Automation and Systems | - |
dc.citation.title | International Conference on Control, Automation and Systems | - |
dc.citation.volume | 2022-November | - |
dc.citation.startPage | 1049 | - |
dc.citation.endPage | 1055 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Automation & Control Systems | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Automation & Control Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | Control system synthesis | - |
dc.subject.keywordPlus | Dynamic mode decomposition | - |
dc.subject.keywordPlus | Mathematical operators | - |
dc.subject.keywordPlus | Vehicles | - |
dc.subject.keywordPlus | Automated driving | - |
dc.subject.keywordPlus | Data driven modeling methods | - |
dc.subject.keywordPlus | Data-driven control | - |
dc.subject.keywordPlus | Data-driven model | - |
dc.subject.keywordPlus | Koopman operator | - |
dc.subject.keywordPlus | Lane keeping | - |
dc.subject.keywordPlus | Linear modeling | - |
dc.subject.keywordPlus | Modelling and controls | - |
dc.subject.keywordPlus | Optimal controls | - |
dc.subject.keywordPlus | Vehicle Control | - |
dc.subject.keywordAuthor | Data-driven control | - |
dc.subject.keywordAuthor | Koopman operator | - |
dc.subject.keywordAuthor | Vehicle control | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/10003764 | - |
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