Recursive prediction error identification and scaling of non-linear state space models using a restricted Black box parameterization
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Publication:2641745
DOI10.1016/j.automatica.2005.08.017zbMath1121.93316OpenAlexW1987800067MaRDI QIDQ2641745
Publication date: 23 August 2007
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.automatica.2005.08.017
samplingstate-space modelsprediction error methodsidentification algorithmsrecursivenon-linear systems
System identification (93B30) Nonlinear systems in control theory (93C10) Control/observation systems governed by ordinary differential equations (93C15)
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Uses Software
Cites Work
- Identification of systems containing linear dynamic and static nonlinear elements
- Adaptive control of Wiener type nonlinear systems
- A case study of Grey Box identification
- Drum-boiler dynamics
- An approach to nonlinear programming
- Representations of non-linear systems: the NARMAX model
- Neural networks for nonlinear dynamic system modelling and identification
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