Aftab, M.S. and Rossiter, J.A. orcid.org/0000-0002-1336-0633 (2022) Predictive functional control for difficult dynamic processes with a simplified tuning mechanism. In: Proceedings of 2022 UKACC 13th International Conference on Control (CONTROL). 2022 UKACC 13th International Conference on Control (CONTROL), 20-22 Apr 2022, Plymouth, UK. Institute of Electrical and Electronics Engineers , pp. 130-135. ISBN 9781665452014
Abstract
Predictive functional control (PFC) is a cheap and simplified model predictive controller, which competes with PID in price and performance. While the tuning process in PFC for simple dynamics is well established and straightforward, it becomes far more ambiguous and often less effective for processes exhibiting challenging behaviour, such as poor damping, instability and/or non-minimum phase characteristics. In this paper, we present a relative PFC algorithm that, when implemented with pre-stabilised prediction dynamics if needed, simplifies performance tuning to merely adjusting one parameter. Furthermore, it provides far superior closed-loop control in practical scenarios, where the conventional PFC and PID fail to perform, as demonstrated with three simulation case studies.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | predictive functional control; pre-stabilisation; 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: | 04 Mar 2022 07:57 |
Last Modified: | 27 May 2023 00:13 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Identification Number: | 10.1109/Control55989.2022.9781444 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:184293 |