A Convex Optimization Framework for Computing Robustness Margins of Kalman Filters
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866914703278604288 |
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| author | Prabhat, Himanshu Bhattacharya, Raktim |
| author_facet | Prabhat, Himanshu Bhattacharya, Raktim |
| contents | This paper proposes a novel convex optimization framework for designing robust Kalman filters that guarantee a user-specified steady-state error while maximizing process and sensor noise. The proposed framework simultaneously determines the Kalman gain and the robustness margin in terms of the process and sensor noise. This is the first paper to present such a joint formulation for Kalman filtering. The proposed methodology is validated through two distinct examples: the Clohessy-Wiltshire-Hill equations for a chaser spacecraft in an elliptical orbit and the longitudinal motion model of an F-16 aircraft. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_02996 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Convex Optimization Framework for Computing Robustness Margins of Kalman Filters Prabhat, Himanshu Bhattacharya, Raktim Systems and Control Optimization and Control Applications This paper proposes a novel convex optimization framework for designing robust Kalman filters that guarantee a user-specified steady-state error while maximizing process and sensor noise. The proposed framework simultaneously determines the Kalman gain and the robustness margin in terms of the process and sensor noise. This is the first paper to present such a joint formulation for Kalman filtering. The proposed methodology is validated through two distinct examples: the Clohessy-Wiltshire-Hill equations for a chaser spacecraft in an elliptical orbit and the longitudinal motion model of an F-16 aircraft. |
| title | A Convex Optimization Framework for Computing Robustness Margins of Kalman Filters |
| topic | Systems and Control Optimization and Control Applications |
| url | https://arxiv.org/abs/2403.02996 |