Parameter estimation algorithms for dynamical response signals based on the multi-innovation theory and the hierarchical principle

In this study, the authors consider the parameter estimation problem of the response signal from a highly non-linear dynamical system. The step response experiment is taken for generating the measured data. Considering the stochastic disturbance in the industrial process and using the gradient searc...

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Veröffentlicht in:	IET signal processing Jg. 11; H. 2; S. 228 - 237
Hauptverfasser:	Xu, Ling, Ding, Feng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 01.04.2017
Schlagworte:	Algorithms decomposition technique dynamical response signal Dynamical systems Estimates estimation theory gradient methods gradient search hierarchical identification algorithm hierarchical principle industrial process Innovation innovation vector interaction estimation theory multiinnovation stochastic gradient algorithm multiinnovation theory nonlinear dynamical system Parameter estimation parameter estimation algorithm Parameters Research Article scalar innovation Scalars signal processing stochastic disturbance stochastic processes Stochasticity estimation theory signal processing parameter estimation algorithm decomposition technique dynamical response signal industrial process multiinnovation stochastic gradient algorithm interaction estimation theory nonlinear dynamical system scalar innovation innovation vector gradient search parameter estimation stochastic disturbance stochastic processes gradient methods multiinnovation theory hierarchical principle hierarchical identification algorithm
ISSN:	1751-9675, 1751-9683, 1751-9683
Online-Zugang:	Volltext
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