Rossiter, J.A. orcid.org/0000-0002-1336-0633, Gonzalez-Villareal, O.J. and Sarbini, M.A.M. (2023) A review of parameterised MPC algorithms. In: Ishii, H., Ebihara, Y., Imura, J. and Yamakita, M., (eds.) IFAC-PapersOnLine. 22nd World Congress of the International Federation of Automatic Control (IFAC2023), 09-14 Jul 2023, Yokohama, Japan. Elsevier , pp. 7692-7697.
Abstract
This paper provides an evaluation and comparison of popular parameterised model predictive control approaches that have been proposed in the literature in recent years. Using the Generalised Predictive Control (GPC) algorithm as the baseline algorithm, the paper sets out a number of performance criteria to compare and contrast with several other MPC approaches. Numerical examples use 100 random samples of 2, 3, and 4-state models and the approaches are compared using the selected performance criteria.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | Predictive control; Model predictive and optimization-based control; Monte Carlo methods |
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: | 24 Mar 2023 11:27 |
Last Modified: | 07 Dec 2023 15:05 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.ifacol.2023.10.1171 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:197625 |