Data-Driven Stabilization of Continuous-Time LTI Systems from Noisy Input-Output Data
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912709485789184 |
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| author | Bosso, Alessandro Borghesi, Marco Iannelli, Andrea Yi, Bowen Notarstefano, Giuseppe |
| author_facet | Bosso, Alessandro Borghesi, Marco Iannelli, Andrea Yi, Bowen Notarstefano, Giuseppe |
| contents | We present an approach to compute stabilizing controllers for continuous-time linear time-invariant systems directly from an input-output trajectory affected by process and measurement noise. The proposed output-feedback design combines (i) an observer of a non-minimal realization of the plant and (ii) a feedback law obtained from a linear matrix inequality (LMI) that depends solely on the available data. Under a suitable interval excitation condition and knowledge of a noise energy bound, the feasibility of the LMI is shown to be necessary and sufficient for stabilizing all non-minimal realizations consistent with the data. We further provide a condition for the feasibility of the LMI related to the signal-to-noise ratio, guidelines to compute the noise energy bound, and numerical simulations that illustrate the effectiveness of the approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_11417 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Data-Driven Stabilization of Continuous-Time LTI Systems from Noisy Input-Output Data Bosso, Alessandro Borghesi, Marco Iannelli, Andrea Yi, Bowen Notarstefano, Giuseppe Systems and Control We present an approach to compute stabilizing controllers for continuous-time linear time-invariant systems directly from an input-output trajectory affected by process and measurement noise. The proposed output-feedback design combines (i) an observer of a non-minimal realization of the plant and (ii) a feedback law obtained from a linear matrix inequality (LMI) that depends solely on the available data. Under a suitable interval excitation condition and knowledge of a noise energy bound, the feasibility of the LMI is shown to be necessary and sufficient for stabilizing all non-minimal realizations consistent with the data. We further provide a condition for the feasibility of the LMI related to the signal-to-noise ratio, guidelines to compute the noise energy bound, and numerical simulations that illustrate the effectiveness of the approach. |
| title | Data-Driven Stabilization of Continuous-Time LTI Systems from Noisy Input-Output Data |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2511.11417 |