Please use this identifier to cite or link to this item: https://doi.org/10.1109/9.788546
Title: Receding horizon recursive state estimation
Authors: Ling, K.V.
Lim, K.W. 
Issue Date: 1999
Source: Ling, K.V., Lim, K.W. (1999). Receding horizon recursive state estimation. IEEE Transactions on Automatic Control 44 (9) : 1750-1753. ScholarBank@NUS Repository. https://doi.org/10.1109/9.788546
Abstract: This paper describes a receding horizon discrete-time state observer using the deterministic least squares framework. The state estimation horizon, which determines the number of past measurement samples used to reconstruct the state vector, is introduced as a tuning parameter for the proposed state observer. A stability result concerning the choice of the state estimation horizon is established. It is also shown that the fixed memory receding horizon state observer can be related to the standard dynamic observer by using an appropriate end-point state weighting on the estimator cost function.
Source Title: IEEE Transactions on Automatic Control
URI: http://scholarbank.nus.edu.sg/handle/10635/62684
ISSN: 00189286
DOI: 10.1109/9.788546
Appears in Collections:Staff Publications

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