An improved observer design approach for autonomous vehicles using error-based ultra-local model
Abstract The paper presents a novel observer design method for an autonomous vehicle-oriented estimation problem. The design process combines two approaches: the Linear Parameter Varying framework and the error-based ultra-local model. The main goal of the error-based ultra-local model is to deal wi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-10575-0 |
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| _version_ | 1849342766840020992 |
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| author | Daniel Fenyes Tamas Hegedus Balazs Nemeth Peter Gaspar |
| author_facet | Daniel Fenyes Tamas Hegedus Balazs Nemeth Peter Gaspar |
| author_sort | Daniel Fenyes |
| collection | DOAJ |
| description | Abstract The paper presents a novel observer design method for an autonomous vehicle-oriented estimation problem. The design process combines two approaches: the Linear Parameter Varying framework and the error-based ultra-local model. The main goal of the error-based ultra-local model is to deal with the uncertainties and the nonlinearities of the model, whose effects cannot be taken into account during the modeling process. In this way, the performance of the LPV-based observer can be significantly improved. The proposed method is implemented for the estimation of the lateral velocity. The efficiency and the operation of the observer algorithm are presented through simulations in CarMaker and using real test measurements from ZalaZone proving ground. |
| format | Article |
| id | doaj-art-a5fa072ab77c4df1a1928a998bd7d4d6 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-a5fa072ab77c4df1a1928a998bd7d4d62025-08-20T03:43:15ZengNature PortfolioScientific Reports2045-23222025-07-0115111610.1038/s41598-025-10575-0An improved observer design approach for autonomous vehicles using error-based ultra-local modelDaniel Fenyes0Tamas Hegedus1Balazs Nemeth2Peter Gaspar3HUN-REN Institute for Computer Science and Control (SZTAKI)HUN-REN Institute for Computer Science and Control (SZTAKI)HUN-REN Institute for Computer Science and Control (SZTAKI)HUN-REN Institute for Computer Science and Control (SZTAKI)Abstract The paper presents a novel observer design method for an autonomous vehicle-oriented estimation problem. The design process combines two approaches: the Linear Parameter Varying framework and the error-based ultra-local model. The main goal of the error-based ultra-local model is to deal with the uncertainties and the nonlinearities of the model, whose effects cannot be taken into account during the modeling process. In this way, the performance of the LPV-based observer can be significantly improved. The proposed method is implemented for the estimation of the lateral velocity. The efficiency and the operation of the observer algorithm are presented through simulations in CarMaker and using real test measurements from ZalaZone proving ground.https://doi.org/10.1038/s41598-025-10575-0 |
| spellingShingle | Daniel Fenyes Tamas Hegedus Balazs Nemeth Peter Gaspar An improved observer design approach for autonomous vehicles using error-based ultra-local model Scientific Reports |
| title | An improved observer design approach for autonomous vehicles using error-based ultra-local model |
| title_full | An improved observer design approach for autonomous vehicles using error-based ultra-local model |
| title_fullStr | An improved observer design approach for autonomous vehicles using error-based ultra-local model |
| title_full_unstemmed | An improved observer design approach for autonomous vehicles using error-based ultra-local model |
| title_short | An improved observer design approach for autonomous vehicles using error-based ultra-local model |
| title_sort | improved observer design approach for autonomous vehicles using error based ultra local model |
| url | https://doi.org/10.1038/s41598-025-10575-0 |
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