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Filtering Approaches for Inequality Constrained Parameter Estimation Open Access


Other title
Moving horizon estimation
Ensemble Kalman filter
Unscented Kalman filter
Inequality constraints
Parameter estimation
Constrained estimation
Type of item
Degree grantor
University of Alberta
Author or creator
Yang, Xiongtan
Supervisor and department
Huang, Biao (Chemical and Materials Engineering)
Prasad, Vinay (Chemical and Materials Engineering)
Examining committee member and department
Trivedi, Japan (Mining and Petroleum Engineering)
Huang, Biao (Chemical and Materials Engineering)
Prasad, Vinay (Chemical and Materials Engineering)
Department of Chemical and Materials Engineering
Chemical Engineering
Date accepted
Graduation date
Master of Science
Degree level
Parameter estimation of a dynamic system is an important task in process systems engineering. The utilization of an augmented system offers the approach of estimating process states and parameters simultaneously. In practice, the parameters often satisfy certain constraints which should be incorporated to improve the estimation performance. This thesis focuses on the inequality constrained parameter estimation problem. We introduce a method of constructing inequality constraints on parameters from routine steady-state operation data. A constraint implementation method with the unscented Kalman filter (UKF) is proposed that yields faster recovery of parameter estimates than the conventional projection method. The appropriate use of projection method with the ensemble Kalman filter (EnKF) is introduced. Also, a constrained estimation method with the EnKF is proposed which results in improved performance compared to the projection method. For the moving horizon estimation (MHE), we propose an alternative approach for constrained parameter estimation, which provides better performance than the directly constrained MHE. The efficacies of the proposed approaches in this thesis are evaluated using several simulated process examples.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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