dc.contributor.author | Dai, Li | |
dc.contributor.author | Cannon, Mark | |
dc.contributor.author | Yang, Fuwen | |
dc.contributor.author | Yan, Shuhao | |
dc.date.accessioned | 2022-01-18T04:47:51Z | |
dc.date.available | 2022-01-18T04:47:51Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 0018-9286 | en_US |
dc.identifier.doi | 10.1109/TAC.2020.3022734 | en_US |
dc.identifier.uri | http://hdl.handle.net/10072/411545 | |
dc.description.abstract | This 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.peerreviewed | Yes | en_US |
dc.language | English | en_US |
dc.publisher | IEEE | en_US |
dc.relation.ispartofpagefrom | 3624 | en_US |
dc.relation.ispartofpageto | 3637 | en_US |
dc.relation.ispartofissue | 8 | en_US |
dc.relation.ispartofjournal | IEEE Transactions on Automatic Control | en_US |
dc.relation.ispartofvolume | 66 | en_US |
dc.subject.fieldofresearch | Applied mathematics | en_US |
dc.subject.fieldofresearch | Electrical engineering | en_US |
dc.subject.fieldofresearch | Mechanical engineering | en_US |
dc.subject.fieldofresearchcode | 4901 | en_US |
dc.subject.fieldofresearchcode | 4008 | en_US |
dc.subject.fieldofresearchcode | 4017 | en_US |
dc.subject.keywords | Science & Technology | en_US |
dc.subject.keywords | Automation & Control Systems | en_US |
dc.subject.keywords | Engineering, Electrical & Electronic | en_US |
dc.title | Fast Self-Triggered MPC for Constrained Linear Systems With Additive Disturbances | en_US |
dc.type | Journal article | en_US |
dc.type.description | C1 - Articles | en_US |
dcterms.bibliographicCitation | Dai, 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. 3624-3637 | en_US |
dc.date.updated | 2022-01-18T04:43:17Z | |
dc.description.version | Accepted 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 |
gro.hasfulltext | Full Text | |
gro.griffith.author | Yang, Fuwen | |