Journal article

Robust targeted exploration for systems with non-stochastic disturbances

Abstract:: We propose a novel targeted exploration strategy designed specifically for uncertain linear time-invariant systems with energybounded disturbances, i.e., without any assumptions on the distribution of the disturbances. We use classical results characterizing the set of non-falsified parameters consistent with energy-bounded disturbances. We derive a semidefinite program which computes an exploration strategy that guarantees a desired accuracy of the parameter estimate. This design is based on sufficient conditions on the spectral content of the exploration data that robustly account for initial parametric uncertainty. Finally, we highlight the applicability of the exploration strategy through a numerical example involving a nonlinear system.

Publication status:: Published

Peer review status:: Peer reviewed

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APA Style

Venkatasubramanian, J., Koehler, J., Cannon, M., & Allgoewer, F. (2026). Robust targeted exploration for systems with non-stochastic disturbances. Automatica, 193.

MLA Style

Venkatasubramanian, J, et al. “Robust Targeted Exploration for Systems with Non-Stochastic Disturbances.” Automatica, vol. 193, 2026.

Chicago Style

Venkatasubramanian, J, J Koehler, M Cannon, and F Allgoewer. 2026. “Robust Targeted Exploration for Systems with Non-Stochastic Disturbances.” Automatica 193.
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Files:: Venkatasubramanian_et_al_2026_Robust_targeted_exploration.html

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Publisher copy:: 10.1016/j.automatica.2026.113228

Authors

+ Venkatasubramanian, J More by this author

Role:: Author

+ Koehler, J More by this author

Role:: Author

+ Cannon, M More by this author

Institution:: University of Oxford
Division:: MPLS
Department:: Engineering Science
Oxford college:: St John's College
Role:: Author
ORCID:: 0000-0003-2189-7876

+ Allgoewer, F More by this author

Role:: Author

+ Deutsche Forschungsgemeinschaft More from this funder

Funder identifier:: https://ror.org/018mejw64
Grant:: 468094890
Programme:: Germany’s Excellence Strategy - EXC 2075 - 390740016

+ Swiss National Science Foundation More from this funder

Funder identifier:: https://ror.org/00yjd3n13
Grant:: 51NF40 180545

Publisher:: Elsevier
Journal:: Automatica More from this journal
Volume:: 193
Article number:: 113228
Publication date:: 2026-08-13
Acceptance date:: 2026-06-12
DOI:: 10.1016/j.automatica.2026.113228
EISSN:: 1873-2836
ISSN:: 0005-1098

Language:: English
Keywords:: experiment design

robust estimation

optimization under uncertainties

uncertainty quantification

data-driven control
Pubs id:: 2433692
Local pid:: pubs:2433692
Deposit date:: 2026-06-15
ARK identifier:: ark:/29072/ora_8d6f2bb2cf7d4092aff3e9614c7c9f8f

Terms of use

Copyright holder:: Venkatasubramanian et al.
Copyright date:: 2026
Rights statement:: © 2026 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Licence:: CC Attribution (CC BY)

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