We provide a convex solution to the robust gain-scheduled estimation problem based on integral quadratic constraints with dynamic D-scalings for both the uncertain and the scheduled component. This closes an important gap since so far merely static scalings or multipliers could be used for the scheduled component in estimation problems. To this end, we provide novel synthesis criteria in terms of linear matrix inequalities for the design of nominal gain-scheduled estimators which allow for a direct combination with available results on robust estimation. We illustrate the benefit of our design approach by means of a numerical example.
%0 Journal Article
%1 HolSch21
%A Holicki, T.
%A Scherer, C. W.
%D 2021
%J EEE Transactions on Automatic Control
%K EXC2075 PN4 PN4-3 selected
%N 11
%P 5592 - 5598
%R 10.1109/TAC.2021.3052751
%T Robust Gain-Scheduled Estimation with Dynamic D-Scalings
%U https://doi.org/10.1109/TAC.2021.3052751
%V 66
%X We provide a convex solution to the robust gain-scheduled estimation problem based on integral quadratic constraints with dynamic D-scalings for both the uncertain and the scheduled component. This closes an important gap since so far merely static scalings or multipliers could be used for the scheduled component in estimation problems. To this end, we provide novel synthesis criteria in terms of linear matrix inequalities for the design of nominal gain-scheduled estimators which allow for a direct combination with available results on robust estimation. We illustrate the benefit of our design approach by means of a numerical example.
@article{HolSch21,
abstract = {We provide a convex solution to the robust gain-scheduled estimation problem based on integral quadratic constraints with dynamic D-scalings for both the uncertain and the scheduled component. This closes an important gap since so far merely static scalings or multipliers could be used for the scheduled component in estimation problems. To this end, we provide novel synthesis criteria in terms of linear matrix inequalities for the design of nominal gain-scheduled estimators which allow for a direct combination with available results on robust estimation. We illustrate the benefit of our design approach by means of a numerical example.},
added-at = {2024-03-26T11:56:16.000+0100},
author = {Holicki, T. and Scherer, C. W.},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/296ea9463e49b1bc584d34ff2ba1fa2ba/exc2075},
doi = {10.1109/TAC.2021.3052751},
file = {:Scherer/2021/HolSch21.pdf:PDF},
interhash = {83fe1838176906c0bb201ee7bd2d2f44},
intrahash = {96ea9463e49b1bc584d34ff2ba1fa2ba},
journal = {EEE Transactions on Automatic Control},
keywords = {EXC2075 PN4 PN4-3 selected},
number = 11,
pages = {5592 - 5598},
timestamp = {2024-03-27T16:35:26.000+0100},
title = {Robust Gain-Scheduled Estimation with Dynamic D-Scalings},
url = {https://doi.org/10.1109/TAC.2021.3052751},
volume = 66,
year = 2021
}
