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Robust MPC for LPV systems via a novel optimization-based constraint tightening

Bujarbaruah, Monimoy and Rosolia, Ugo and Stürz, Yvonne R. and Zhang, Xiaojing and Borrelli, Francesco (2022) Robust MPC for LPV systems via a novel optimization-based constraint tightening. Automatica, 143 . Art. No. 110459. ISSN 0005-1098. doi:10.1016/j.automatica.2022.110459.

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We propose a novel approach to design a robust Model Predictive Controller (MPC) for constrained uncertain linear systems. The uncertain system is modeled as linear parameter varying with an additive disturbance. Set bounds for the system matrices and the additive uncertainty are assumed to be known. We formulate a novel optimization-based constraint tightening strategy around a predicted nominal trajectory which utilizes these bounds. With an appropriately designed terminal cost function and constraint set, we prove robust satisfaction of the imposed constraints by the resulting MPC in closed-loop with the uncertain system, and Input to State Stability of the origin. We highlight the efficacy of our proposed approach via a numerical example.

Item Type:Article
Related URLs:
URLURL TypeDescription
Rosolia, Ugo0000-0002-1682-0551
Stürz, Yvonne R.0000-0001-5729-8491
Zhang, Xiaojing0000-0002-6998-3792
Borrelli, Francesco0000-0001-8919-6430
Additional Information:© 2022 Elsevier. Received 13 September 2020, Revised 3 January 2022, Accepted 15 May 2022, Available online 11 July 2022, Version of Record 11 July 2022. We thank prof. Diego Muñoz Carpintero for sharing his software and his invaluable help in comparing the proposed approach with his algorithm.
Subject Keywords:Robust MPC; Linear systems; Parametric model uncertainty; Convex optimization
Record Number:CaltechAUTHORS:20220712-372667000
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Official Citation:Monimoy Bujarbaruah, Ugo Rosolia, Yvonne R. Stürz, Xiaojing Zhang, Francesco Borrelli, Robust MPC for LPV systems via a novel optimization-based constraint tightening, Automatica, Volume 143, 2022, 110459, ISSN 0005-1098,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:115497
Deposited By: George Porter
Deposited On:13 Jul 2022 19:10
Last Modified:25 Jan 2023 00:31

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