Nonlinear State Estimation with Missing Observations Based on Mathematical Programming

0353841 - ÚTIA 2011 CZ eng A - Abstract
Pavelková, Lenka
Nonlinear State Estimation with Missing Observations Based on Mathematical Programming.
Abstracts of contributions of the 6th Int. Workshop on Data - Algorithms - Decision Making 2010. Praha: ÚTIA AV ČR, 2010 - (Janžura, M.; Ivánek, J.). s. 23-23
[6th International Workshop on Data – Algorithms – Decision Making. 02.12.2010-04.12.2010, Jindřichův Hradec]
R&D Projects: GA MŠMT 1M0572
Institutional research plan: CEZ:AV0Z10750506
Keywords : state filtering * bounded errors * missing measurements
Subject RIV: BC - Control Systems Theory
http://library.utia.cas.cz/separaty/2010/AS/pavelkova-nonlinear state estimation with missing observations based on mathematical programming.pdf

The contribution deals with two problems in the state estimation: a bounded uncertainty and missing measurement data. A discrete time state-space model with uniformly distributed uncertainty is considered. The Bayesian approach is used and maximum a posteriori probability estimates are evaluated. An estimation algorithm is based on the non-linear programming.
Permanent Link: http://hdl.handle.net/11104/0192972