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Minimum-variance reduced-order estimation algorithms from Pontrygin's minimum principleA uniform derivation of minimum-variance reduced-order (MVRO) filter-smoother algorithms from Pontrygin's Minimum Principle is presented. An appropriate performance index for a general class of reduced order estimation problem is formulated herein to yield optimal results over the entire time interval of estimation. These results provide quantitative criteria for measuring the performance of certain classes of heuristically designed, suboptimal reduced-order estimators as well as explicit guidance to the suboptimal filter design process with both continuous and discrete filter-smoother algorithms being considered. By the duality principle, the algorithms of reduced-order estimation can be easily extended to the deterministic problems of optimal control (i.e., the regulator and linear tracking problem).
Document ID
19900000789
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Ebrahimi, Yaghoob S.
(Boeing Commercial Airplane Co. Seattle, WA, United States)
Date Acquired
September 6, 2013
Publication Date
May 1, 1989
Publication Information
Publication: NASA. Langley Research Center, Proceedings of the Workshop on Computational Aspects in the Control of Flexible Systems, Part 2
Subject Category
Spacecraft Design, Testing And Performance
Accession Number
90N10105
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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