Impulse response constrained LS-SVM modelling for MIMO Hammerstein system identification

DOI10.1080/00207179.2017.1373862zbMath1416.93052OpenAlexW2754428841MaRDI QIDQ5382603

Oscar Mauricio Agudelo, Ricardo Castro-Garcia, Johan A. K. Suykens

Publication date: 18 June 2019

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

Full work available at URL: https://doi.org/10.1080/00207179.2017.1373862

zbMATH Keywords

system identificationHammerstein systemsimpulse responseMIMOLS-SVM

Mathematics Subject Classification ID

System identification (93B30) Multivariable systems, multidimensional control systems (93C35)

Related Items (2)

Identification of Hammerstein–Wiener models with hysteresis front nonlinearities ⋮ Multi‐innovation Newton recursive methods for solving the support vector machine regression problems

Uses Software

• Wiener-Hammerstein Benchmark

Cites Work

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• Identification of nonlinear systems using neural networks and polynomial models. A block-oriented approach.
• Block-oriented nonlinear system identification
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• A new method for the identification of Hammerstein model
• Identification of MIMO Hammerstein models using least squares support vector machines
• Structure identification of nonlinear dynamic systems - A survey on input/output approaches
• Uniqueness of a basic nonlinear structure
• Identifying MIMO Hammerstein systems in the context of subspace model identification methods
• Frequency domain identification of hammerstein models

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