Observability and State Estimation for Smooth and Nonsmooth Differential Algebraic Equation Systems
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| Format: | Preprint |
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2025
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| _version_ | 1866914104275369984 |
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| author | Abdelfattah, Hesham Eisa, Sameh A. Stechlinski, Peter |
| author_facet | Abdelfattah, Hesham Eisa, Sameh A. Stechlinski, Peter |
| contents | In this work, we extend the sensitivity-based rank condition (SERC) test for local observability to another class of systems, namely smooth and nonsmooth differential-algebraic equation (DAE) systems of index-1. The newly introduced test for DAEs, which we call the lexicographic SERC (L-SERC) observability test, utilizes the theory of lexicographic differentiation to compute sensitivity information. Moreover, the newly introduced L-SERC observability test is useful in the context of partial observability as it can judge which states are observable and which are not. Additionally, we introduce a novel sensitivity-based extended Kalman filter (S-EKF) algorithm for state estimation, applicable to both smooth and nonsmooth DAE systems. Finally, we apply the newly developed S-EKF to estimate the states of a wind turbine power system model. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2508_18476 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Observability and State Estimation for Smooth and Nonsmooth Differential Algebraic Equation Systems Abdelfattah, Hesham Eisa, Sameh A. Stechlinski, Peter Dynamical Systems In this work, we extend the sensitivity-based rank condition (SERC) test for local observability to another class of systems, namely smooth and nonsmooth differential-algebraic equation (DAE) systems of index-1. The newly introduced test for DAEs, which we call the lexicographic SERC (L-SERC) observability test, utilizes the theory of lexicographic differentiation to compute sensitivity information. Moreover, the newly introduced L-SERC observability test is useful in the context of partial observability as it can judge which states are observable and which are not. Additionally, we introduce a novel sensitivity-based extended Kalman filter (S-EKF) algorithm for state estimation, applicable to both smooth and nonsmooth DAE systems. Finally, we apply the newly developed S-EKF to estimate the states of a wind turbine power system model. |
| title | Observability and State Estimation for Smooth and Nonsmooth Differential Algebraic Equation Systems |
| topic | Dynamical Systems |
| url | https://arxiv.org/abs/2508.18476 |