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Article Dans Une Revue Systems and Control Letters Année : 2022

An interval-valued recursive estimation framework for linearly parameterized systems

Résumé

This paper proposes a recursive interval-valued estimation framework for identifying the parameters of linearly parameterized systems which may be slowly time-varying. It is assumed that the model error (which may consist in measurement noise or model mismatch or both) is unknown but lies at each time instant in a known interval. In this context, the proposed method relies on bounding the error generated by a given reference point-valued recursive estimator, for example, the well-known recursive least squares algorithm. We discuss the trade-off between computational complexity and tightness of the estimated parametric interval.
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Dates et versions

hal-04083209 , version 1 (27-04-2023)

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Laurent Bako, Seydi Ndiaye, Eric Blanco. An interval-valued recursive estimation framework for linearly parameterized systems. Systems and Control Letters, 2022, 168, pp.105345. ⟨10.1016/j.sysconle.2022.105345⟩. ⟨hal-04083209⟩
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