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Reduced minimax state estimation

Abstract : A reduced minimax state estimation approach is proposed for high-dimensional models. It is based on the reduction of the ordinary differential equation with high state space dimension to the low-dimensional Differential-Algebraic Equation (DAE) and on the subsequent application of the minimax state estimation to the resulting DAE. The DAE is composed of a reduced state equation and of a linear algebraic constraint. The later allows to bound linear combinations of the reduced state's components in order to prevent possible instabilities, originating from the model reduction. The method is robust as it can handle model and observational errors in any shape, provided they are bounded. We derive a minimax algorithm adapted to computations in high-dimension. It allows to compute both the state estimate and the reachability set in the reduced space.
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Submitted on : Wednesday, December 29, 2010 - 9:38:27 PM
Last modification on : Wednesday, October 26, 2022 - 8:16:21 AM
Long-term archiving on: : Monday, November 5, 2012 - 3:02:08 PM


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  • HAL Id : inria-00550729, version 1


Vivien Mallet, Sergiy Zhuk. Reduced minimax state estimation. [Research Report] RR-7500, INRIA. 2010, pp.23. ⟨inria-00550729⟩



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