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conference paper
State estimation with uncertain parametric models
2000
Proceedings of the 8th IEEE Mediterranean Conference on Control & Automation
This paper develops robust estimation algorithms for state-space models that are subject to bounded parametric uncertainties. Compared with existing robust filters, the new filters perform data regulaarization rather than de-regularization and they do not require existence conditions. The resulting filter structures also turn out to be similar to various (time- and measurement-update, prediction, and information) forms of the Kalman filter, albeit ones that operate on corrected parameters rather than on the given nominal parameters.
Type
conference paper
Authors
Publication date
2000
Published in
Proceedings of the 8th IEEE Mediterranean Conference on Control & Automation
Peer reviewed
REVIEWED
EPFL units
Event name | Event place | Event date |
Rio, Greece | June, 2000 | |
Available on Infoscience
January 4, 2018
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