Unbiased parameter estimation of linear systems in the presence of input and output noise

DOI10.1002/acs.4480030303zbMath0733.93077OpenAlexW2123169126MaRDI QIDQ3360766

Wei Xing Zheng, Chun-Bo Feng

Publication date: 1989

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.4480030303

zbMATH Keywords

recursive algorithmbatch algorithmleast-squares estimation method

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10) Least squares and related methods for stochastic control systems (93E24) Identification in stochastic control theory (93E12)

Related Items (16)

Recursive identification for dynamic linear systems from noisy input-output measurements ⋮ A bias-correction method for indirect identification of closed-loop systems ⋮ Subspace algorithms for the identification of multivariable dynamic errors-in-variables models ⋮ Identification of errors in variables linear state space models using iterative principal component analysis ⋮ Algorithms for recursive/semi-recursive bias-compensating least squares system identification within the errors-in-variables framework ⋮ Identification of closed-loop systems with low-order controllers ⋮ Accuracy analysis of bias-eliminating least squares estimates for errors-in-variables systems ⋮ Parameter consistency and quadratically constrained errors-in-variables least-squares identification ⋮ Accuracy analysis of time domain maximum likelihood method and sample maximum likelihood method for errors-in-variables and output error identification ⋮ A graph subspace approach to system identification based on errors-in-variables system models ⋮ Errors-in-variables methods in system identification ⋮ Bias-compensation-based least-squares estimation with a forgetting factor for output error models with white noise ⋮ Relations between bias-eliminating least squares, the Frisch scheme and extended compensated least squares methods for identifying errors-in-variables systems ⋮ Matrix pencils and existence conditions for quadratic programming with a sign-indefinite quadratic equality constraint ⋮ Bias-eliminating least-squares identification of errors-in-variables models with mutually correlated noises ⋮ Optimal errors-in-variables filtering

Cites Work

• Identification of linear systems with input and output noise: the Koopmans-Levin method
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