Identification of multivariable bilinear state space systems based on subspace techniques and separable least squares optimization

DOI10.1080/00207170110089806zbMath1101.93308OpenAlexW2119495590MaRDI QIDQ3151513

Vincent Verdult, Verhaegen, Michel

Publication date: 16 October 2002

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

Full work available at URL: https://doi.org/10.1080/00207170110089806

Mathematics Subject Classification ID

Related Items (9)

Subspace identification of multivariable linear parameter-varying systems ⋮ An algorithm of uniform ultimate boundedness for a class of switched linear systems ⋮ Expectation-maximization algorithm for bilinear systems by using the Rauch-Tung-Striebel smoother ⋮ Application of model-free LQG subspace predictive control to TCP congestion control ⋮ Variational Bayesian identification for bilinear state space models with Markov‐switching time delays ⋮ Identification of non-linear parametrically varying models using separable least squares ⋮ Kernel methods for subspace identification of multivariable LPV and bilinear systems ⋮ Identification of discrete-time state affine state space models using cumulants ⋮ Identification of multivariable bilinear state space systems based on subspace techniques and separable least squares optimization

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