The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
An Accelerated Dual Gradient-Projection Algorithm for Embedded Linear Model Predictive Control
Abstract
This paper proposes a dual fast gradient-projection method for solving quadratic programming problems that arise in model predictive control of linear systems subject to general polyhedral constraints on inputs and states. The proposed algorithm is well suited for embedded control applications in that: 1) it is extremely simple and easy to code; 2) the number of iterations to reach a given accuracy in terms of optimality and feasibility of the primal solution can be tightly estimated; and 3) the computational cost per iteration increases only linearly with the prediction horizon.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
Beck, A., & Teboulle, M. (2009) · SIAM Journal on Imaging Sciences · doi:10.1137/080716542 · Cited by 11,952
Cited by
Reference and command governors for systems with constraints: A survey on theory and applications
Garone, E., Di Cairano, S., & Kolmanovsky, I. (2017) · Automatica · doi:10.1016/j.automatica.2016.08.013 · Cited by 466
Metadata
- Authors
- Patrinos, P., & Bemporad, A.
- Venue
- IEEE Transactions on Automatic Control
- Published
- 2014-01
- Volume
- 59
- Issue
- 1
- Pages
- 18-33
- ISSN
- 0018-9286 (ISSN-L)
- 1558-2523
- OpenAlex
- W1981832695
- Cited by
- 287
- References
- 1
- FWCI
- 44.72
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An Accelerated Dual Gradient-Projection Algorithm for Embedded Linear Model Predictive Control. https://app.cochat.ai/papers/10.1109/tac.2013.2275667
- The paper
- Patrinos, P., & Bemporad, A. (2014). An Accelerated Dual Gradient-Projection Algorithm for Embedded Linear Model Predictive Control. IEEE Transactions on Automatic Control. https://doi.org/10.1109/tac.2013.2275667
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
