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Schiller, Julian D. ; Grüne, Lars ; Müller, Matthias A.:
Optimal state estimation : Turnpike analysis and performance results.
Bayreuth ; Hannover
,
2024
. - 8 S.
DOI: https://doi.org/10.48550/arXiv.2409.14873
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| Projekttitel: |
Offizieller Projekttitel Projekt-ID Stochastic Optimal Control and MPC – Dissipativity, Risk and Performance GR 1569/25-1, BA 7477/3-1, project no. 499435839 Robuste Stabilität und Suboptimalität bei der Zustandsschätzung mit bewegtem Horizont---Von konzeptionellen zu praktisch relevanten Garantien project no. 426459964 |
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| Projektfinanzierung: |
Deutsche Forschungsgemeinschaft |
Abstract
In this paper, we introduce turnpike arguments in the context of optimal state estimation. In particular, we show that the optimal solution of the state estimation problem involving all available past data serves as turnpike for the solutions of truncated problems involving only a subset of the data. We consider two different mathematical characterizations of this phenomenon and provide corresponding sufficient conditions that rely on strict dissipativity and decaying sensitivity. As second contribution, we show how a specific turnpike property can be used to establish performance guarantees when approximating the optimal solution of the full problem by a sequence of truncated problems, and we show that the resulting performance (both averaged and non-averaged) is approximately optimal with error terms that can be made arbitrarily small by an appropriate choice of the horizon length. In addition, we discuss interesting implications of these results for the practically relevant case of moving horizon estimation and illustrate our results with a numerical example.