Remote state estimation problem:Towards the data-rate limit along the avenue of the second Lyapunov method

Christoph Kawan, A. Matveev, A.Y. (Sasha) Pogromskiy (Corresponding author)

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)

Abstract

In the context of control and estimation under information constraints, restoration entropy measures the minimal required data rate above which the state of a system can be estimated so that the estimation quality does not degrade over time and, conversely, can be improved. The remote observer here is assumed to receive its data through a communication channel of finite bit-rate capacity. In this paper, we provide a new characterization of the restoration entropy which does not require to compute any temporal limit, i.e., an asymptotic quantity. Our new formula is based on the idea of finding a specific Riemannian metric on the state space which makes the metric-dependent upper estimate of the restoration entropy as tight as one wishes.
Original languageEnglish
Article number109467
Number of pages12
JournalAutomatica
Volume125
Issue numberMarch
DOIs
Publication statusPublished - Mar 2021

Funding

A. Pogromsky acknowledges his partial support by the UCoCoS project which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 675080 . A. Matveev acknowledges his support by the Ministry of Science and Higher Education of the Russian Federation (appl. 2020-220-08-4683 ). C. Kawan is supported by the German Research Foundation (DFG) through the grant ZA 873/4-1 . A preliminary version of this paper was presented at the 2020 IFAC World Congress ( Kawan, Matveev, & Pogromsky, 2020 ).

FundersFunder number
Horizon 2020 Framework Programme
Marie Skłodowska‐Curie675080
Deutsche ForschungsgemeinschaftZA 873/4-1
Ministry of Science and Higher Education of the Russian Federation2020-220-08-4683

    Keywords

    • Entropy
    • Finite bit-rates
    • First and second Lyapunov methods
    • Nonlinear systems
    • Remote state estimation

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