A blind approach to closed-loop identification of Hammerstein systems

DOI10.1080/00207170601026505zbMath1140.93350OpenAlexW1998710981WikidataQ57582916 ScholiaQ57582916MaRDI QIDQ3423789

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Publication date: 15 February 2007

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207170601026505

Mathematics Subject Classification ID

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

Related Items (8)

Gradient-based recursive identification methods for input nonlinear equation error closed-loop systems ⋮ Least squares algorithm for an input nonlinear system with a dynamic subspace state space model ⋮ Multi-innovation stochastic gradient identification for Hammerstein controlled autoregressive autoregressive systems based on the filtering technique ⋮ Parameter estimation algorithms for Hammerstein output error systems using Levenberg-Marquardt optimization method with varying interval measurements ⋮ Blind identification of non-minimum phase ARMA systems ⋮ Recursive maximum likelihood method for the identification of Hammerstein ARMAX system ⋮ Identification of Hammerstein systems without explicit parameterisation of non-linearity ⋮ Identification of Hammerstein systems with continuous nonlinearity

Cites Work

• Identification of nonlinear systems using neural networks and polynomial models. A block-oriented approach.
• Automatic tuning of simple regulators with specifications on phase and amplitude margins
• Blind identifiability of IIR systems
• Identification of linear systems with hard input nonlinearities of known structure
• Nonlinear auto-tune identification

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