Error analysis on the initial state reconstruction problem
In this paper, we propose a method to estimate the initial state of a linear dynamical system from noisy observation based on Kalman Filters and Optimal Smoothing techniques. The method allows the user to have estimations in real-time, that is, to have a new estimation for each new observation. More...
Main Authors: | Martin, R.D (Author), Medri, I. (Author), Osorio, J. (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
Birkhauser
2023
|
Subjects: | |
Online Access: | View Fulltext in Publisher View in Scopus |
Similar Items
-
Navigation algorithms and observability analysis for formation flying missions
by: Huxel, Paul John
Published: (2008) -
An evaluation of the moving horizon estimation algorithm for online estimation of battery state of charge and state of health
by: Bibin Nataraja, Pattel
Published: (2015) -
Comparisons on Kalman-Filter-Based Dynamic State Estimation Algorithms of Power Systems
by: Hui Liu, et al.
Published: (2020-01-01) -
Adaptive quasi-dynamic state estimation for MV and LV grids
by: Natallia Makarava, et al.
Published: (2019-08-01) -
SYNTHESIS OF MODEL THE LUENBERGER OBSERVER FOR EXTERNAL CYLINDRICAL GRINDING PROCESS
by: Sergey BRATAN, et al.
Published: (2013-05-01)