Systematic Estimation of Noise Statistics for Nonlinear State Estimators by Parametric Uncertainty

An easy-to-implement noise estimation method for tuning state estimators is proposed. It outperforms benchmark methods in terms of accuracy or computational cost both in theory and in a case study. We assume parametric uncertainty in the process model, which we transform into noise statistics using...

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Veröffentlicht in:	Industrial & engineering chemistry research 2024-06, Vol.63 (22), p.9887-9903
Hauptverfasser:	Krog, Halvor Aarnes, Jäschke, Johannes
Format:	Artikel
Sprache:	eng
Schlagworte:	case studies chemistry covariance Process Systems Engineering uncertainty
Online-Zugang:	Volltext
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