Combined frequency-prediction error identification approach for Wiener systems with backlash and backlash-inverse operators

DOI10.1016/j.automatica.2013.12.030zbMath1298.93340OpenAlexW2135110161MaRDI QIDQ462344

Adil Brouri, Fouad Giri, Fatima-Zahra Chaoui, Abdelhadi Radouane

Publication date: 20 October 2014

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2013.12.030

zbMATH Keywords

system identificationprediction error methodbacklach nonlinearitiesfrequency approachWiener systems

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Least squares and related methods for stochastic control systems (93E24) Identification in stochastic control theory (93E12) Stochastic systems in control theory (general) (93E03)

Related Items (10)

Identification of Hammerstein–Wiener models with hysteresis front nonlinearities ⋮ Modified multi-innovation stochastic gradient algorithm for Wiener-Hammerstein systems with backlash ⋮ Recursive least squares algorithm and gradient algorithm for Hammerstein-Wiener systems using the data filtering ⋮ Boundary adaptive fault-tolerant control for a flexible Timoshenko arm with backlash-like hysteresis ⋮ Identification of block-oriented nonlinear systems starting from linear approximations: a survey ⋮ System identification of a class of Wiener systems with hysteretic nonlinearities ⋮ Wiener–Hammerstein nonlinear system identification using spectral analysis ⋮ Sampled-data adaptive observer for state-affine systems with uncertain output equation ⋮ Two-stage instrumental variables identification of polynomial Wiener systems with invertible nonlinearities ⋮ Modelling and identification of nonlinear cascade systems with backlash input and static output nonlinearities

Cites Work

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• MINLIP for the identification of monotone Wiener systems
• Identifying MIMO Wiener systems using subspace model identification methods
• Towards identification of Wiener systems with the least amount of a priori information: IIR cases
• Recusrsive prediction error identification using the nonlinear Wiener model
• Linear and nonlinear system identification using separable least-squares
• Frequency domain identification of Wiener models
• Uniquely connecting frequency domain representations of given order polynomial Wiener-Hammerstein systems
• Frequency identification of nonparametric Wiener systems containing backlash nonlinearities
• Recursive identification algorithm for dynamic systems with output backlash and its convergence
• Nonparametric System Identification
• Convergence analysis of recursive identification algorithms based on the nonlinear Wiener model
• Frequency domain system identification with missing data
• Blind Maximum-Likelihood Identification of Wiener Systems
• An Analytic Geometry Approach to Wiener System Frequency Identification
• Recursive subspace identification of linear and nonlinear Wiener state-space models
• Parameter identification of Wiener systems with discontinuous nonlinearities

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