A reinforcement learning-based approach for optimal output tracking in uncertain nonlinear systems with mismatched disturbances

Tang, Z., Rossiter, J.A. orcid.org/0000-0002-1336-0633 and Panoutsos, G. orcid.org/0000-0002-7395-8418 (2024) A reinforcement learning-based approach for optimal output tracking in uncertain nonlinear systems with mismatched disturbances. In: 2024 UKACC 14th International Conference on Control (CONTROL). CONTROL 2024: 14th United Kingdom Automatic Control Council (UKACC) International Conference on Control, 10-12 Apr 2024, Winchester, United Kingdom. Institute of Electrical and Electronics Engineers , pp. 169-174. ISBN 979-8-3503-7427-8

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Item Type: Proceedings Paper
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© 2024 The author(s). Except as otherwise noted, this author-accepted version of a paper published in UKACC International Conference on Control (CONTROL) is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: Uncertainty; Simulation; Measurement uncertainty; Optimal control; Reinforcement learning; Mathematical models; Robustness
Dates:
  • Published: 22 May 2024
  • Published (online): 22 May 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering
Funding Information:
Funder
Grant number
Engineering and Physical Sciences Research Council
EP/V051261/1
Depositing User: Symplectic Sheffield
Date Deposited: 27 Nov 2024 09:32
Last Modified: 02 Dec 2024 12:50
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Refereed: Yes
Identification Number: 10.1109/control60310.2024.10532060
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