Hierarchical identification for multivariate Hammerstein systems by using the modified Kalman filter

The parameter estimation problem for multi-input multi-output Hammerstein systems is considered. For the Hammerstein model to be identified, its dynamic time-invariant subsystem is described by a controlled autoregressive model with a communication delay. The modified Kalman filter (MKF) algorithm i...

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Veröffentlicht in:	IET control theory & applications Jg. 11; H. 6; S. 857 - 869
Hauptverfasser:	Ma, Junxia, Xiong, Weili, Chen, Jing, Feng, Ding
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 14.04.2017
Schlagworte:	Algorithms autoregressive processes communication delay controlled autoregressive model convergence analysis delays dynamic time‐invariant subsystem Dynamical systems Estimates hierarchical identification Kalman filters least squares approximations Mathematical models MIMO systems MKF‐based hierarchical LS algorithm MKF‐based recursive least squares algorithm modified Kalman filter multiinput multioutput Hammerstein system multivariate Hammerstein system Parameter estimation Parameter identification Parameter modification Parameters Research Article MKF-based recursive least squares algorithm least squares approximations controlled autoregressive model dynamic time-invariant subsystem hierarchical identification autoregressive processes modified Kalman filter communication delay multivariate Hammerstein system MIMO systems convergence analysis MKF-based hierarchical LS algorithm delays parameter estimation multiinput multioutput Hammerstein system Kalman filters
ISSN:	1751-8644, 1751-8652
Online-Zugang:	Volltext
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