Robust fixed-lag smoothing under model perturbations
Optimization and Control
2022-11-01 v1
Abstract
A robust fixed-lag smoothing approach is proposed in the case there is a mismatch between the nominal model and the actual model. The resulting robust smoother is characterized by a dynamic game between two players: one player selects the least favorable model in a prescribed ambiguity set, while the other player selects the fixed-lag smoother minimizing the smoothing error with respect to least favorable model. We propose an efficient implementation of the proposed smoother. Moreover, we characterize the corresponding least favorable model over a finite time horizon. Finally, we test the robust fixed-lag smoother in two examples. The first one regards a target tracking problem, while the second one regards a parameter estimation problem.
Cite
@article{arxiv.2210.16802,
title = {Robust fixed-lag smoothing under model perturbations},
author = {Shenglun Yi and Mattia Zorzi},
journal= {arXiv preprint arXiv:2210.16802},
year = {2022}
}