Two nonlinear optimization methods for black box identification compared

DOI10.1016/j.automatica.2010.06.021zbMath1204.93125OpenAlexW2002142240MaRDI QIDQ608476

Anne Van Mulders, Johan Schoukens, Marnix Volckaert, Moritz Diehl

Publication date: 25 November 2010

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://lirias.kuleuven.be/handle/123456789/305216

zbMATH Keywords

parameter estimationnonlinear systemsnonlinear modelsstate-space modelsconstraintsidentification algorithms

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) 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

Identification of Wiener-Hammerstein systems by a nonparametric separation of the best linear approximation, Two nonlinear optimization methods for black box identification compared, Identification of block-oriented nonlinear systems starting from linear approximations: a survey, Maximum likelihood estimation of Gaussian models with missing data -- Eight equivalent formulations, On the smoothness of nonlinear system identification

Uses Software

• Wiener-Hammerstein Benchmark

Cites Work

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