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dc.contributor.authorDai, Li
dc.contributor.authorCannon, Mark
dc.contributor.authorYang, Fuwen
dc.contributor.authorYan, Shuhao
dc.date.accessioned2022-01-18T04:47:51Z
dc.date.available2022-01-18T04:47:51Z
dc.date.issued2021
dc.identifier.issn0018-9286en_US
dc.identifier.doi10.1109/TAC.2020.3022734en_US
dc.identifier.urihttp://hdl.handle.net/10072/411545
dc.description.abstractThis article proposes a robust self-triggered model predictive control (MPC) algorithm for a class of constrained linear systems subject to bounded additive disturbances, in which the intersampling time is determined by a fast convergence self-triggered mechanism. The main idea of the self-triggered mechanism is to select a sampling interval so that a rapid decrease in the predicted costs associated with optimal predicted control inputs is guaranteed. This allows for a reduction in the required computation without compromising performance. By using a constraint tightening technique and exploring the nature of the open-loop control between sampling instants, a set of minimally conservative constraints is imposed on nominal states to ensure robust constraint satisfaction. A multistep open-loop MPC optimization problem is formulated, which ensures recursive feasibility for all possible realizations of the disturbance. The closed-loop system is guaranteed to satisfy a mean-square stability condition. To further reduce the computational load, when states reach a predetermined neighborhood of the origin, the control law of the robust self-triggered MPC algorithm switches to a self-triggered local controller. A compact set in the state space is shown to be robustly asymptotically stabilized. Numerical comparisons are provided to demonstrate the effectiveness of the proposed strategies.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglishen_US
dc.publisherIEEEen_US
dc.relation.ispartofpagefrom3624en_US
dc.relation.ispartofpageto3637en_US
dc.relation.ispartofissue8en_US
dc.relation.ispartofjournalIEEE Transactions on Automatic Controlen_US
dc.relation.ispartofvolume66en_US
dc.subject.fieldofresearchApplied mathematicsen_US
dc.subject.fieldofresearchElectrical engineeringen_US
dc.subject.fieldofresearchMechanical engineeringen_US
dc.subject.fieldofresearchcode4901en_US
dc.subject.fieldofresearchcode4008en_US
dc.subject.fieldofresearchcode4017en_US
dc.subject.keywordsScience & Technologyen_US
dc.subject.keywordsAutomation & Control Systemsen_US
dc.subject.keywordsEngineering, Electrical & Electronicen_US
dc.titleFast Self-Triggered MPC for Constrained Linear Systems With Additive Disturbancesen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dcterms.bibliographicCitationDai, L; Cannon, M; Yang, F; Yan, S, Fast Self-Triggered MPC for Constrained Linear Systems With Additive Disturbances, IEEE Transactions on Automatic Control, 2021, 66 (8), pp. 3624-3637en_US
dc.date.updated2022-01-18T04:43:17Z
dc.description.versionAccepted Manuscript (AM)en_US
gro.rights.copyright© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.en_US
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gro.griffith.authorYang, Fuwen


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