A novel control paradigm for large-scale hybrid networks

Informations projet

CLariNet

N° de convention de subvention: 101018826

DOI

10.3030/101018826

Date de signature de la CE 5 Mai 2021

Date de début 1 Octobre 2021

Date de fin 30 Septembre 2026

Financé au titre de

• EXCELLENT SCIENCE - European Research Council (ERC)

Coût total

€ 2 500 000,00

Contribution de l’UE

€ 2 500 000,00

Coordonné par

TECHNISCHE UNIVERSITEIT DELFT
Netherlands

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Open Research Data Pilot (1)

Data Management Plan

Report on how results data and publications will be made open access available under FAIR conditions

Publications

Peer reviewed articles (19)

On the Regret of Model Predictive Control With Imperfect Inputs

Auteurs: Changrui Liu, Shengling Shi, Bart De Schutter
Publié dans: IEEE Control Systems Letters, Numéro 9, 2025, Page(s) 601-606, ISSN 2475-1456
Éditeur: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/lcsys.2025.3577083

Multi-agent reinforcement learning via distributed MPC as a function approximator

Auteurs: Mallick, Samuel; Airaldi, Filippo; Dabiri, Azita; De Schutter, Bart
Publié dans: Automatica, Numéro 4, 2024, Page(s) 111803, ISSN 0005-1098
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2024.111803

Distributed Model Predictive Control for Piecewise Affine Systems Based on Switching ADMM

Auteurs: Samuel Mallick, Azita Dabiri, Bart De Schutter
Publié dans: IEEE Transactions on Automatic Control, Numéro 70, 2025, Page(s) 3727-3741, ISSN 0018-9286
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tac.2024.3512334

Reinforcement Learning With Model Predictive Control for Highway Ramp Metering

Auteurs: Filippo Airaldi, Bart De Schutter, Azita Dabiri
Publié dans: IEEE Transactions on Intelligent Transportation Systems, Numéro 26, 2025, Page(s) 5988-6004, ISSN 1524-9050
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2025.3549227

Approximate dynamic programming for constrained linear systems: A piecewise quadratic approximation approach

Auteurs: He, Kanghui; Shi, Shengling; Boom, Ton van den; De Schutter, Bart
Publié dans: Automatica, Numéro 160, 2024, Page(s) 111456, ISSN 0005-1098
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2023.111456

Bi-level model predictive control for metro networks: Integration of timetables, passenger flows, and train speed profiles

Auteurs: Xiaoyu Liu; Azita Dabiri; Jing Xun; Bart De Schutter
Publié dans: Transportation Research Part E: Logistics and Transportation Review, Numéro 180, 2023, Page(s) 103339, ISSN 1366-5545
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.tre.2023.103339

A combined probabilistic-fuzzy approach for dynamic modeling of traffic in smart cities: Handling imprecise and uncertain traffic data

Auteurs: A. Jamshidnejad and B. De Schutter
Publié dans: Computers and Electrical Engineering, 2024, Page(s) 109552, ISSN 0045-7906
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.compeleceng.2024.109552

Deep Learning for Object Detection and Segmentation in Videos: Toward an Integration With Domain Knowledge

Auteurs: A. Ilioudi, A. Dabiri, B. J. Wolf and B. De Schutter
Publié dans: IEEE Access, Numéro 10, 2022, Page(s) 34562-34576, ISSN 2169-3536
Éditeur: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2022.3162827

Distributed Model Predictive Control for Virtually Coupled Heterogeneous Trains: Comparison and Assessment

Auteurs: Xiaoyu Liu, Azita Dabiri, Yihui Wang, Jing Xun, Bart De Schutter
Publié dans: IEEE Transactions on Intelligent Transportation Systems, Numéro 25, 2024, Page(s) 20753-20766, ISSN 1524-9050
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2024.3458169

Adaptive parameterized model predictive control based on reinforcement learning: A synthesis framework

Auteurs: D. Sun, A. Jamshidnejad, and B. De Schutter
Publié dans: Engineering Applications of Artificial Intelligence, 2024, Page(s) 109009, ISSN 0952-1976
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.engappai.2024.109009

Modeling and Efficient Passenger-Oriented Control for Urban Rail Transit Networks

Auteurs: Xiaoyu Liu; Azita Dabiri; Yihui Wang; Bart De Schutter
Publié dans: IEEE Transactions on Intelligent Transportation Systems, Numéro 24, 2023, Page(s) 3325-3338, ISSN 1524-9050
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2022.3228340

Learning-Based MPC for Fuel Efficient Control of Autonomous Vehicles With Discrete Gear Selection

Auteurs: Samuel Mallick, Gianpietro Battocletti, Qizhang Dong, Azita Dabiri, Bart De Schutter
Publié dans: IEEE Control Systems Letters, Numéro 9, 2025, Page(s) 1117-1122, ISSN 2475-1456
Éditeur: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/lcsys.2025.3575335

Finite-sample analysis of identification of switched linear systems with arbitrary or restricted switching

Auteurs: Shengling Shi; Othmane Mazhar; Bart De Schutter
Publié dans: IEEE Control Systems Letters, Numéro 7, 2023, Page(s) 121-126, ISSN 2475-1456
Éditeur: IEEE
DOI: 10.48550/arxiv.2203.09862

A Novel Framework Combining MPC and Deep Reinforcement Learning With Application to Freeway Traffic Control

Auteurs: Dingshan Sun; Anahita Jamshidnejad; Bart De Schutter
Publié dans: IEEE Transactions on Intelligent Transportation Systems, 2024, Page(s) 6756-6769, ISSN 1524-9050
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2023.3342651

Grammatical-Evolution-based parameterized Model Predictive Control for urban traffic networks

Auteurs: Joost Jeschke; Dingshan Sun; Anahita Jamshidnejad; Bart De Schutter
Publié dans: Control Engineering Practice, Numéro 132, 2023, Page(s) 105431, ISSN 0967-0661
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.conengprac.2022.105431

Real-Time Train Scheduling With Uncertain Passenger Flows: A Scenario-Based Distributed Model Predictive Control Approach

Auteurs: Xiaoyu Liu; Azita Dabiri; Yihui Wang; Bart De Schutter
Publié dans: IEEE Transactions on Intelligent Transportation Systems, Numéro 25, 2024, Page(s) 4219-4232, ISSN 1524-9050
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2023.3329445

Reinforcement learning-based model predictive control for greenhouse climate control

Auteurs: Samuel Mallick, Filippo Airaldi, Azita Dabiri, Congcong Sun, Bart De Schutter
Publié dans: Smart Agricultural Technology, Numéro 10, 2025, Page(s) 100751, ISSN 2772-3755
Éditeur: Elsevier BV
DOI: 10.1016/j.atech.2024.100751

A Novel Bi-Level Temporally-Distributed Mpc Approach: An Application to Green Urban Mobility

Auteurs: Anahita Jamshidnejad; Dingshan Sun; Antonella Ferrara; Bart De Schutter
Publié dans: Transportation Research Part C: Emerging Technologies, Numéro 156, 2023, Page(s) 104334, ISSN 0968-090X
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.trc.2023.104334

Sensitivity analysis for piecewise-affine approximations of nonlinear programs with polytopic constraints

Auteurs: L. Gharavi; C. Liu; B. De Schutter; and S. Baldi
Publié dans: IEEE Control Systems Letters, 2024, Page(s) 1271-1276, ISSN 2475-1456
Éditeur: IEEE
DOI: 10.1109/lcsys.2024.3408711

Conference proceedings (12)

Regret Analysis of Learning-Based Linear Quadratic Gaussian Control with Additive Exploration

Auteurs: Athrey, Archith; Mazhar, Othmane; Guo, Meichen; De Schutter, Bart; Shi, Shengling
Publié dans: Proceedings of the 2024 European Control Conference, 2024, Page(s) 1795-1801
Éditeur: -
DOI: 10.23919/ecc64448.2024.10590739

Scenario-Based MPC for Real-Time Passenger-Centric Timetable Scheduling of Urban Rail Transit Networks

Auteurs: Liu, X. (author); Dabiri, A. (author); De Schutter, B.H.K. (author)
Publié dans: Proceedings of the 22nd IFAC World Congress / IFAC-PapersOnLine, 2023, Page(s) 2347-2352
Éditeur: IFAC / Elsevier
DOI: 10.1016/j.ifacol.2023.10.1205

Integrated reinforcement learning and optimization for railway timetable rescheduling

Auteurs: H. Zhang, X. Liu, D. Sun, A. Dabiri, and B. De Schutter
Publié dans: Proceedings of the 17th IFAC Symposium on Control in Transportation Systems (CTS 2024, 2024, Page(s) 310-315
Éditeur: -
DOI: 10.1016/j.ifacol.2024.07.358

A Generalized Partitioning Strategy for Distributed Control

Auteurs: Alessandro Riccardi, Luca Laurenti, Bart De Schutter
Publié dans: 2024 IEEE 63rd Conference on Decision and Control (CDC), 2025, Page(s) 6134-6141
Éditeur: IEEE
DOI: 10.1109/cdc56724.2024.10885848

Adaptive Parameterized Control for Coordinated traffic Management Using Reinforcement Learning

Auteurs: Sun, D. (author); Jamshidnejad, A. (author); De Schutter, B.H.K. (author)
Publié dans: Proceedings of the 22nd IFAC World Congress / IFAC-PapersOnLine, 2023, Page(s) 5463-5468
Éditeur: IFAC / Elsevier
DOI: 10.1016/j.ifacol.2023.10.198

Stability and Performance Analysis of Model Predictive Control of Uncertain Linear Systems

Auteurs: Changrui Liu, Shengling Shi, Bart De Schutter
Publié dans: 2024 IEEE 63rd Conference on Decision and Control (CDC), 2025, Page(s) 7356-7362
Éditeur: IEEE
DOI: 10.1109/cdc56724.2024.10885798

Signal selection for local module identification in linear dynamic networks: A graphical approach

Auteurs: Shengling Shi, Xiaodong Cheng, Bart De Schutter, Paul M.J. Van den Hof
Publié dans: Proceedings of the 22nd IFAc World Congress / IFAC-PapersOnLine, 2023, Page(s) 2407-2412
Éditeur: IFAC / Elsevier
DOI: 10.1016/j.ifacol.2023.10.1215

Provably-Stable Stochastic MPC for a Class of Nonlinear Contractive Systems

Auteurs: Cordiano, F. (author); Fochesato, Marta (author); Huang, Linbin (author); De Schutter, B.H.K. (author)
Publié dans: Proceedings of the 22nd IFAC World Congress / IFAC-PapersOnLine, 2023, Page(s) 11242-11248
Éditeur: IFAC
DOI: 10.1016/j.ifacol.2023.10.313

Efficient and Safe Learning-based Control of Piecewise Affine Systems Using Optimization-Free Safety Filters*

Auteurs: Kanghui He, Shengling Shi, Ton Van Den Boom, Bart De Schutter
Publié dans: 2024 IEEE 63rd Conference on Decision and Control (CDC), 2025, Page(s) 5046-5053
Éditeur: IEEE
DOI: 10.1109/cdc56724.2024.10886328

A Behavioral Perspective on Models of Linear Dynamical Networks with Manifest Variables

Auteurs: S. Shi, Z. Sun, and B. De Schutter
Publié dans: Proceedings of the 2024 European Control Conference, 2024, Page(s) 2927-2933
Éditeur: -
DOI: 10.23919/ecc64448.2024.10591178

Scenario reduction with guarantees for stochastic optimal control of linear systems

Auteurs: F. Cordiano; B. De Schutter
Publié dans: Proceedings of the 2024 European Control Conference, 2024, Page(s) 3502-3508
Éditeur: -
DOI: 10.23919/ecc64448.2024.10590866

Learning safety in model-based Reinforcement Learning using MPC and Gaussian Processes

Auteurs: Airaldi, Filippo; De Schutter, Bart; Dabiri, Azita
Publié dans: Proceedings of the 22nd IFAC World Congress / Elsevier, 2023, Page(s) 5759-5764
Éditeur: IFAC / Elsevier
DOI: 10.1016/j.ifacol.2023.10.563

Book chapters (1)

A Benchmark for the Application of Distributed Control Techniques to the Electricity Network of the European Economic Area

Auteurs: Alessandro Riccardi, Luca Laurenti, Bart De Schutter
Publié dans: Advances in Industrial Control, Control Systems Benchmarks, 2025, Page(s) 9-28
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-76312-0_2