The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Guidelines for the Design of Finite Control Set Model Predictive Controllers
Abstract
Direct model predictive control (MPC) with reference tracking, also referred to as finite control set MPC (FCS-MPC), has gained significant attention in recent years, mainly from the academic community. Thanks to its applicability to a wide range of power electronic systems, it is considered a promising control method for such systems. However, to simplify the design, researchers frequently make choices that-often unknowingly-reduce the system performance. In this article, we discuss and analyze the factors that affect the closed-loop performance of FCS-MPC. Based on these findings, design guidelines are provided that help to maximize the system performance. To highlight the performance benefits, two case studies will be considered: the first one consists of a two-level converter and an induction machine, whereas the second one adds an LC filter between the converter and the machine.
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
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Model predictive control: Theory and practice—A survey
García, C. E., Prett, D. M., & Morari, M. (1989) · Automatica · doi:10.1016/0005-1098(89)90002-2 · Cited by 5,284
A survey of industrial model predictive control technology
Qin, S. J., & Badgwell, T. A. (2003) · Control Engineering Practice · doi:10.1016/s0967-0661(02)00186-7 · Cited by 5,099
A New Quick-Response and High-Efficiency Control Strategy of an Induction Motor
Takahashi, I., & Noguchi, T. (1986) · IEEE Transactions on Industry Applications · doi:10.1109/tia.1986.4504799 · Cited by 3,407
Nemhauser, G. L., & Wolsey, L. A. (1972) · Cited by 3,371
Computer controlled systems theory and design
(1986) · Automatica · doi:10.1016/0005-1098(86)90095-6 · Cited by 3,003
Model Predictive Control for Power Converters and Drives: Advances and Trends
Vazquez, S., Rodriguez, J., Rivera, M., Franquelo, L. G., & Norambuena, M. (2017) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2016.2625238 · Cited by 1,859
State of the Art of Finite Control Set Model Predictive Control in Power Electronics
Rodriguez, J., Kazmierkowski, M. P., Espinoza, J. R., Zanchetta, P., Abu-Rub, H., Young, H. A., & Rojas, C. A. (2013) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2012.2221469 · Cited by 1,802
Predictive Control in Power Electronics and Drives
Cortés, P., Kaźmierkowski, M. P., Kennel, R. M., Quevedo, D. E., & Rodríguez, J. (2008) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2008.2007480 · Cited by 1,752
Predictive Current Control of a Voltage Source Inverter
Rodriguez, J., Pontt, J., Silva, C. A., Correa, P., Lezana, P., Cortes, P., & Ammann, U. (2007) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2006.888802 · Cited by 1,563
Cited by
Model predictive control of microgrids – An overview
Hu, J., Shan, Y., Guerrero, J. M., Ioinovici, A., Chan, K. W., & Rodriguez, J. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.110422 · Cited by 451
Metadata
- Authors
- Karamanakos, P., & Geyer, T.
- Venue
- IEEE Transactions on Power Electronics
- Published
- 2020-07
- Volume
- 35
- Issue
- 7
- Pages
- 7434-7450
- ISSN
- 0885-8993 (ISSN-L)
- 1941-0107
- OpenAlex
- W2989892707
- Cited by
- 585
- References
- 45
- FWCI
- 20.09
- 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: Guidelines for the Design of Finite Control Set Model Predictive Controllers. https://app.cochat.ai/papers/10.1109/tpel.2019.2954357
- The paper
- Karamanakos, P., & Geyer, T. (2020). Guidelines for the Design of Finite Control Set Model Predictive Controllers. IEEE Transactions on Power Electronics. https://doi.org/10.1109/tpel.2019.2954357
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.
