Hernandez Vicente, B.A. orcid.org/0000-0003-0701-5590 and Trodden, P.A. orcid.org/0000-0002-8787-7432 (2019) Stabilizing predictive control with persistence of excitation for constrained linear systems. Systems and Control Letters, 126. pp. 58-66. ISSN 0167-6911
Abstract
A new adaptive predictive controller for constrained linear systems is presented. The main feature of the proposed controller is the partition of the input in two components. The first part is used to persistently excite the system, in order to guarantee accurate and convergent parameter estimates in a deterministic framework. An MPC-inspired receding horizon optimization problem is developed to achieve the required excitation in a manner that is optimal for the plant. The remaining control action is employed by a conventional tube MPC controller to regulate the plant in the presence of parametric uncertainty and the excitation generated for estimation purposes. Constraint satisfaction, robust exponential stability, and convergence of the estimates are guaranteed under design conditions mildly more demanding than that of standard MPC implementations.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Elsevier. This is an author produced version of a paper subsequently published in Systems and Control Letters. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | adaptive control; model predictive control; control of constrained systems; system identification; persistent excitation |
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: | 25 Mar 2019 10:02 |
Last Modified: | 28 Mar 2020 01:38 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.sysconle.2019.03.003 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:143742 |