Combined state and multi-innovation parameter estimation for an input non-linear state-space system using the key term separation

In this study, the authors study the state and parameter estimation problem for an input non-linear system consisting of a static non-linear block and a linear time-invariant state space subsystem. Using the filtering technique, a filtering based multi-innovation generalised stochastic gradient (SG)...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	IET control theory & applications Ročník 10; číslo 13; s. 1503 - 1512
Hlavní autori:	Wang, Xuehai, Ding, Feng, Hayat, Tasawar, Alsaedi, Ahmed
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	The Institution of Engineering and Technology 29.08.2016
Predmet:	Algorithms Computer simulation Dynamical systems Filtering filtering based multiinnovation generalised stochastic gradient algorithm Filtration gradient methods input nonlinear system key term separation linear systems linear time‐invariant state space subsystem multiinnovation generalised SG algorithm multiinnovation parameter estimation problem nonlinear state‐space system nonlinear systems Nonlinearity Parameter estimation redundant parameters Regular Papers Separation state estimation problem state‐space methods key term separation linear systems state estimation problem nonlinear state-space system multiinnovation parameter estimation problem nonlinear systems redundant parameters multiinnovation generalised SG algorithm parameter estimation filtering based multiinnovation generalised stochastic gradient algorithm linear time-invariant state space subsystem gradient methods state-space methods input nonlinear system
ISSN:	1751-8644, 1751-8652
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!