Ramesh, N., Kerrigan, E.C. and Nie, Y. (2024) Tracking-in-range formulations for numerical optimal control. In: IFAC-PapersOnLine. 8th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2024), 21-24 Aug 2024, Kyoto, Japan. Elsevier BV , pp. 53-58.
Abstract
In contrast to set-point tracking which aims to reduce the tracking error between the tracker and the reference, tracking-in-range problems only focus on whether the tracker is within a given range around the reference, making it more suitable for the mission specifications of many practical applications. In this work, we present novel optimal control formulations to solve tracking-in-range problems, for problems requiring the tracker to be always in range, as well as problems allowing the tracker to go out of range, which yield overall better outcomes. Since the problem naturally involves discontinuous functions, we present alternative formulations and regularisation strategies to improve the performance of numerical solvers. The extension to in-range tracking with multiple trackers and in-range tracking in high-dimensional space are also discussed and illustrated with numerical examples, demonstrating substantial increases in mission performance in comparison to traditional set-point tracking.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | Optimal Control; Nonlinear Model Predictive Control; Intelligent Vehicles |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Oct 2024 13:52 |
Last Modified: | 08 Oct 2024 13:53 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.ifacol.2024.09.009 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:218085 |