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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Bibliographic Details
Published in:	Automatica (Oxford) Vol. 45; no. 1; pp. 25 - 33
Main Authors:	Bell, Bradley M., Burke, James V., Pillonetto, Gianluigi
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 2009 Elsevier
Subjects:	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 Access:	Get full text
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