The feasibility of parametric approaches to predictive control when using far future feed forward information

Dughman, S.S. and Rossiter, J.A. orcid.org/0000-0002-1336-0633 (2017) The feasibility of parametric approaches to predictive control when using far future feed forward information. In: 2017 13th IEEE International Conference on Control & Automation (ICCA). 13th IEEE International Conference on Control and Automation, 03/07/2017 - 06/07/2017, Ohrid, Macedonia. Institute of Electrical and Electronics Engineers .

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Copyright, Publisher and Additional Information: © 2017 IEEE. This is an author produced version of a paper subsequently published in 2017 13th IEEE International Conference on Control & Automation (ICCA). Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Parametric predictive control; advance knowledge; computational efficiency
Dates:
  • Accepted: 17 March 2017
  • Published (online): 8 August 2017
  • Published: 8 August 2017
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: 23 Mar 2017 10:06
Last Modified: 03 Nov 2017 01:55
Published Version: https://doi.org/10.1109/ICCA.2017.8003215
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Refereed: Yes
Identification Number: https://doi.org/10.1109/ICCA.2017.8003215

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