Least-squares identification of a class of multivariable systems with correlated disturbances

DOI10.1016/S0016-0032(99)00038-1zbMath0967.93093OpenAlexW2068980959MaRDI QIDQ5926855

Wei Xing Zheng

Publication date: 19 August 2001

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0016-0032(99)00038-1

zbMATH Keywords

system identificationleast-squares methodcorrelated noisemultivariable systemsunbiased estimations

Mathematics Subject Classification ID

Least squares and related methods for stochastic control systems (93E24) Identification in stochastic control theory (93E12)

Related Items (11)

Stochastic gradient algorithm for multi-input multi-output Hammerstein FIR-MA-like systems using the data filtering ⋮ Maximum likelihood based recursive parameter estimation for controlled autoregressive ARMA systems using the data filtering technique ⋮ Hierarchical least-squares based iterative identification for multivariable systems with moving average noises ⋮ Multi-innovation least squares identification methods based on the auxiliary model for MISO systems ⋮ Several gradient parameter estimation algorithms for dual-rate sampled systems ⋮ The data-filtering based bias compensation recursive least squares identification for multi-input single-output systems with colored noises ⋮ Unbiased identification of a class of multi-input single-output systems with correlated disturbances using bias compensation methods ⋮ Hierarchical estimation algorithms for multivariable systems using measurement information ⋮ Parameter consistency and quadratically constrained errors-in-variables least-squares identification ⋮ Bias-compensation-based least-squares estimation with a forgetting factor for output error models with white noise ⋮ Multi-innovation stochastic gradient algorithm for multiple-input single-output systems using the auxiliary model

Cites Work

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• On a least-squares-based algorithm for identification of stochastic linear systems
• Bias correction in least-squares identification
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• Parametrizations of linear dynamical systems: Canonical forms and identifiability
• On-line modified least-squares parameter estimation of linear discrete dynamic systems
• Design of optimal input signals for the identification of distributed parameter systems †
• Consistent parameter estimation of systems disturbed by correlated noise
• Study of a bias-free least squares parameter estimator

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