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MEMBERS OF RESEARCH CENTER
Research Centre
Data - Algorithms - Decision Making
Data - Algorithms - Decision Making
Established in 2005 under support of MŠMT ČR (project 1M0572)
Publications
Multiple-model filtering with multiple constraints
Typ:
Conference paper
Authors:
Proceedings name:
Proceedings of the 2010 American Control Conference
Serie:
Baltimore, USA
Year:
2010
Pages:
6858-6863
ISBN:
978-1-4244-7425-7
ISSN:
0743-1619
URL (www page):
attachment1:
clanek_ACC10.pdf [file]
attachment2:
prezentace_ACC10.pdf [file]
Anotation:
The paper deals with state estimation of nonlinear stochastic systems, where the state is subject to nonlinear equality constraints reflecting some physical or technological limitations. Usually, this problem of constrained state estimation is solved within the Kalman filtering framework. The goal of the paper is to provide a generalization of the solution to a multiplemodel multiple-constraint problem, where the two-step method for constraint application is adopted. In addition, the model weight computation is analyzed and a weight correction for the constrained estimation is proposed. The proposed method is illustrated in a numerical example.