Hammerstein-Wiener system estimator initialization

DOI10.1016/j.automatica.2004.03.018zbMath1055.93017OpenAlexW1982716475MaRDI QIDQ1881194

Philippe Crama, Johan Schoukens

Publication date: 4 October 2004

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2004.03.018

zbMATH Keywords

convergence analysisnonlinear system identificationiterative identification

Mathematics Subject Classification ID

System identification (93B30) Nonlinear systems in control theory (93C10)

Related Items (10)

Identification of non-uniformly sampled Wiener systems with dead-zone non-linearities ⋮ Identification of nonlinear dynamic systems with input saturation and output backlash using three-block cascade models ⋮ A nonparametric kernel-based approach to Hammerstein system identification ⋮ Identification of block-oriented nonlinear systems starting from linear approximations: a survey ⋮ Tracking control of soft dielectric elastomer actuator based on nonlinear PID controller ⋮ Some stochastic gradient algorithms for Hammerstein systems with piecewise linearity ⋮ Separability of scalar random multisine signals ⋮ Nonlinear system identification using fractional Hammerstein-Wiener models ⋮ Improved differential evolutionary algorithm for nonlinear identification of a novel vibration‐assisted swing cutting system ⋮ Parametric identification of parallel Wiener-Hammerstein systems

Cites Work

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• Identification of systems containing linear dynamic and static nonlinear elements
• A blind approach to the Hammerstein-Wiener model identification
• Estimation of an N-L-N Hammerstein-Wiener model
• Generation of enhanced initial estimates for Hammerstein systems
• Subspace-based methods for the identification of linear time-invariant systems
• Asymptotic properties of least-squares estimates of Hammerstein-Wiener models
• Non-linear system identification using the Hammerstein model
• A nonparametric polynomial identification algorithm for the Hammerstein system
• Parametric and nonparametric identification of linear systems in the presence of nonlinear distortions-a frequency domain approach
• Frequency domain system identification with missing data
• Spectral analysis of block structured non-linear systems

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