Long-Horizon Direct Model Predictive Control with Reduced Computational Complexity

Mattia Rossi; Petros Karamanakos; Arto Sankala

doi:10.1109/PRECEDE57319.2023.10174519

Long-Horizon Direct Model Predictive Control with Reduced Computational Complexity

Mattia Rossi, Petros Karamanakos, Arto Sankala

Sähkötekniikka

Tutkimustuotos: Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

1 Sitaatiot (Scopus)

10 Lataukset (Pure)

Abstrakti

The paper proposes a strategy that reduces the computational burden of enumeration-based direct model predictive control (MPC) with long prediction intervals. This is achieved by combining a move blocking scheme with an educated restriction of the set of candidate solutions. To demonstrate the effectiveness of the proposed algorithm, a two-level converter connected to the grid via an LCL filter serves as a case study.

Alkuperäiskieli	Englanti
Otsikko	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
Kustantaja	IEEE
Sivumäärä	6
ISBN (elektroninen)	979-8-3503-9686-7
ISBN (painettu)	979-8-3503-9687-4
DOI - pysyväislinkit	https://doi.org/10.1109/PRECEDE57319.2023.10174519
Tila	Julkaistu - 2023
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics - Wuhan, Kiina Kesto: 16 kesäk. 2023 → 19 kesäk. 2023

Conference

Conference	IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics
Maa/Alue	Kiina
Kaupunki	Wuhan
Ajanjakso	16/06/23 → 19/06/23

Rahoitus

ACKNOWLEDGEMENT The authors would like to acknowledge the financial support from the Tandem Industry Academia (TIA) funding program of the Finnish Research Impact Foundation (FRIF).

Julkaisufoorumi-taso

Jufo-taso 1

!!ASJC Scopus subject areas

Control and Optimization
Modelling and Simulation
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Mechanical Engineering
Safety, Risk, Reliability and Quality

Pääsy asiakirjaan

10.1109/PRECEDE57319.2023.10174519

Long-Horizon Direct Model Predictive Control
This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Accepted author manuscript, 1,54 MBLisenssi: Unspecified

https://urn.fi/URN:NBN:fi:tuni-202309078015Lisenssi: Unspecified

Siteeraa tätä

@inproceedings{bdb43d1434c64492a8b745361fc295d8,

title = "Long-Horizon Direct Model Predictive Control with Reduced Computational Complexity",

abstract = "The paper proposes a strategy that reduces the computational burden of enumeration-based direct model predictive control (MPC) with long prediction intervals. This is achieved by combining a move blocking scheme with an educated restriction of the set of candidate solutions. To demonstrate the effectiveness of the proposed algorithm, a two-level converter connected to the grid via an LCL filter serves as a case study.",

keywords = "grid-connected converter, integer programming, LCL filter, Model predictive control (MPC), optimal control",

author = "Mattia Rossi and Petros Karamanakos and Arto Sankala",

note = "Funding Information: ACKNOWLEDGEMENT The authors would like to acknowledge the financial support from the Tandem Industry Academia (TIA) funding program of the Finnish Research Impact Foundation (FRIF). Publisher Copyright: {\textcopyright} 2023 IEEE.; IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics ; Conference date: 16-06-2023 Through 19-06-2023",

year = "2023",

doi = "10.1109/PRECEDE57319.2023.10174519",

language = "English",

isbn = "979-8-3503-9687-4",

booktitle = "2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023",

publisher = "IEEE",

address = "United States",

}

Rossi, M, Karamanakos, P & Sankala, A 2023, Long-Horizon Direct Model Predictive Control with Reduced Computational Complexity. julkaisussa 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. IEEE, IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, Wuhan, Kiina, 16/06/23. https://doi.org/10.1109/PRECEDE57319.2023.10174519

TY - GEN

T1 - Long-Horizon Direct Model Predictive Control with Reduced Computational Complexity

AU - Rossi, Mattia

AU - Karamanakos, Petros

AU - Sankala, Arto

N1 - Funding Information: ACKNOWLEDGEMENT The authors would like to acknowledge the financial support from the Tandem Industry Academia (TIA) funding program of the Finnish Research Impact Foundation (FRIF). Publisher Copyright: © 2023 IEEE.

PY - 2023

Y1 - 2023

N2 - The paper proposes a strategy that reduces the computational burden of enumeration-based direct model predictive control (MPC) with long prediction intervals. This is achieved by combining a move blocking scheme with an educated restriction of the set of candidate solutions. To demonstrate the effectiveness of the proposed algorithm, a two-level converter connected to the grid via an LCL filter serves as a case study.

AB - The paper proposes a strategy that reduces the computational burden of enumeration-based direct model predictive control (MPC) with long prediction intervals. This is achieved by combining a move blocking scheme with an educated restriction of the set of candidate solutions. To demonstrate the effectiveness of the proposed algorithm, a two-level converter connected to the grid via an LCL filter serves as a case study.

KW - grid-connected converter

KW - integer programming

KW - LCL filter

KW - Model predictive control (MPC)

KW - optimal control

U2 - 10.1109/PRECEDE57319.2023.10174519

DO - 10.1109/PRECEDE57319.2023.10174519

M3 - Conference contribution

AN - SCOPUS:85166209833

SN - 979-8-3503-9687-4

BT - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

PB - IEEE

T2 - IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics

Y2 - 16 June 2023 through 19 June 2023

ER -

Long-Horizon Direct Model Predictive Control with Reduced Computational Complexity

Abstrakti

Conference

Rahoitus

Julkaisufoorumi-taso

!!ASJC Scopus subject areas

Pääsy asiakirjaan

Sormenjälki

Siteeraa tätä