Bin Abdullah, M. and Rossiter, J. orcid.org/0000-0002-1336-0633 (2019) Using Laguerre functions to improve the tuning and performance of predictive functional control. International Journal of Control, 94 (1). pp. 202-214. ISSN 0020-7179
Abstract
This paper proposes a novel modification to the predictive functional control (PFC) algorithm to facilitate significant improvements in the tuning efficacy. The core concept is the use of an alternative parameterisation of the degrees of freedom in the PFC law. Building on recent insights into the potential of Laguerre functions in traditional MPC (Rossiter et al., 2010; Wang, 2009), the paper develops an appropriate framework for PFC and then demonstrates that these functions can be exploited to allow easier and more effective tuning in PFC as well as facilitating strong constraint handling properties. The proposed design approach and the associated tuning methodology are developed and their efficacy is demonstrated with a number of numerical examples.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Taylor & Francis. |
Keywords: | MPC; PFC; coincidence horizon; tuning |
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: | 11 Mar 2019 09:52 |
Last Modified: | 18 Nov 2021 13:48 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.1080/00207179.2019.1589650 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:142935 |