An inequality constrained nonlinear Kalman–Bucy smoother by interior point likelihood maximization

Kalman–Bucy smoothers are often used to estimate the state variables as a function of time in a system with stochastic dynamics and measurement noise. This is accomplished using an algorithm for which the number of numerical operations grows linearly with the number of time points. All of the random...

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Veröffentlicht in:	Automatica (Oxford) Jg. 45; H. 1; S. 25 - 33
Hauptverfasser:	Bell, Bradley M., Burke, James V., Pillonetto, Gianluigi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Kidlington Elsevier Ltd 2009 Elsevier
Schlagworte:	Applied sciences Computer science; control theory; systems Control theory. Systems Exact sciences and technology Function estimation Inequality constrained systems Interior point applications Kalman filter Modelling and identification State estimation Function estimation Interior point applications Inequality constrained systems State estimation Kalman filter Maximization Interior point method Dynamical system Modeling Optimization Uncertain system Gaussian process Inequality constraint System identification Non deterministic system State constraint Signal to noise ratio
ISSN:	0005-1098, 1873-2836
Online-Zugang:	Volltext
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