The relationship between a continuous-time identification algorithm based on the deterministic filter and least-squares methods

DOI10.1016/0020-0255(79)90008-2zbMath0451.93060OpenAlexW1964817909MaRDI QIDQ1148283

S. H. Smith

Publication date: 1979

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0020-0255(79)90008-2

zbMATH Keywords

Kalman filterstate estimatorrecursive algorithms

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12) Model systems in control theory (93C99)

Cites Work

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• The identification of the parameters of time-invariant stochastic systems by a method derived from the continuous-time Kalman filter
• The analysis of a parameter identification algorithm which was derived from the continuous time Kalman filter
• A study in continuous time of the identification of initial conditions and/or parameters of deterministic system by means of a Kalman-type filter
• An exact equivalence between the discrete- and continuous-time formulations of the Kalman filter
• A Kalman filter type of extension to a deterministic gradient technique for parameter estimation
• System identification. A survey
• A study of the Kalman filter as a state estimator of deterministic and stochastic systems
• Numerical identification of continuous-time systems
• Identification in the presence of initial conditions

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