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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.20259 |
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| _version_ | 1866915985295933440 |
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| author | Wolff, Tobias M. Krauss, Isabelle Lopez, Victor G. Müller, Matthias A. |
| author_facet | Wolff, Tobias M. Krauss, Isabelle Lopez, Victor G. Müller, Matthias A. |
| contents | In this work, we introduce a sample- and data-based moving horizon estimation framework for linear systems. We perform state estimation in a sample-based fashion in the sense that we assume to have only few, irregular output measurements available. This setting is encountered in applications where measuring is expensive or time-consuming. Furthermore, the state estimation framework does not rely on a standard mathematical model, but on an implicit system representation based on measured data. We prove sample-based practical robust exponential stability of the proposed estimator under mild assumptions. Furthermore, we apply the proposed scheme to estimate the states of a gastrointestinal tract absorption system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_20259 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Data-based Moving Horizon Estimation under Irregularly Measured Data Wolff, Tobias M. Krauss, Isabelle Lopez, Victor G. Müller, Matthias A. Systems and Control In this work, we introduce a sample- and data-based moving horizon estimation framework for linear systems. We perform state estimation in a sample-based fashion in the sense that we assume to have only few, irregular output measurements available. This setting is encountered in applications where measuring is expensive or time-consuming. Furthermore, the state estimation framework does not rely on a standard mathematical model, but on an implicit system representation based on measured data. We prove sample-based practical robust exponential stability of the proposed estimator under mild assumptions. Furthermore, we apply the proposed scheme to estimate the states of a gastrointestinal tract absorption system. |
| title | Data-based Moving Horizon Estimation under Irregularly Measured Data |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2512.20259 |