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Paula Chanfreut
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2020 – today
- 2023
- [c7]Stefan van Dijk, Paula Chanfreut, W. P. M. H. Heemels:
Decentralized Design for LQ Consensus in Multi-Agent Systems. CDC 2023: 7427-7432 - [c6]Paula Chanfreut, José M. Maestre, Dinesh Krishnamoorthy, Eduardo F. Camacho:
ALADIN-Based Distributed Model Predictive Control with Dynamic Partitioning: An Application to Solar Parabolic Trough Plants. CDC 2023: 8376-8381 - [c5]Tobias Heins, Paula Chanfreut, Sriram Karthik Gurumurthy, Priyank Srivastava, Antonello Monti, Anuradha M. Annaswamy:
Distributed Frequency Divider-based Model Predictive Control for Frequency Control of Multi-Area Power Systems. SmartGridComm 2023: 1-7 - [i3]Paula Chanfreut, José María Maestre, Dinesh Krishnamoorthy, Eduardo F. Camacho:
ALADIN-based Distributed Model Predictive Control with dynamic partitioning: An application to Solar Parabolic Trough Plants. CoRR abs/2305.02821 (2023) - 2022
- [j8]Teresa Arauz, Paula Chanfreut
, José María Maestre Torreblanca
:
Cyber-security in networked and distributed model predictive control. Annu. Rev. Control. 53: 338-355 (2022) - [j7]Ana Sánchez-Amores
, Paula Chanfreut, José María Maestre, Eduardo Fernández Camacho
:
Coalitional model predictive control with different inter-agent interaction modes. Eur. J. Control 68: 100676 (2022) - [j6]Paula Chanfreut
, José María Maestre
, Antonio Ferramosca
, Francisco Javier Muros
, Eduardo F. Camacho
:
Distributed Model Predictive Control for Tracking: A Coalitional Clustering Approach. IEEE Trans. Autom. Control. 67(12): 6873-6880 (2022) - [j5]Paula Chanfreut
, José María Maestre
, Takeshi Hatanaka
, Eduardo F. Camacho
:
Fast Clustering for Multi-agent Model Predictive Control. IEEE Trans. Control. Netw. Syst. 9(3): 1544-1555 (2022) - [c4]Paula Chanfreut, José M. Maestre, Eduardo F. Camacho, Francesco Borrelli
:
Collaborative learning model predictive control for repetitive tasks. CDC 2022: 5291-5296 - [i2]Paula Chanfreut, José María Maestre, Eduardo F. Camacho, Francesco Borrelli
:
Collaborative learning model predictive control for repetitive tasks. CoRR abs/2211.16633 (2022) - 2021
- [j4]Paula Chanfreut
, José María Maestre
, Eduardo F. Camacho:
A survey on clustering methods for distributed and networked control systems. Annu. Rev. Control. 52: 75-90 (2021) - [j3]Paula Chanfreut
, José María Maestre
, Francisco Javier Muros
, Eduardo F. Camacho
:
Clustering Switching Regions for Feedback Controllers: A Convex Approach. IEEE Trans. Control. Netw. Syst. 8(4): 1730-1742 (2021) - [j2]María Isabel Fernández, Paula Chanfreut
, Isabel Jurado
, José María Maestre
:
A Data-Based Model Predictive Decision Support System for Inventory Management in Hospitals. IEEE J. Biomed. Health Informatics 25(6): 2227-2236 (2021) - [j1]Paula Chanfreut
, José María Maestre
, Eduardo F. Camacho
:
Coalitional Model Predictive Control on Freeways Traffic Networks. IEEE Trans. Intell. Transp. Syst. 22(11): 6772-6783 (2021) - [c3]Paula Chanfreut, Ana Sánchez-Amores
, Jose Maria Maestre, Eduardo F. Camacho:
Distributed Model Predictive Control based on Dual Decomposition with Neural-Network-based Warm Start. ECC 2021: 1969-1974 - [i1]Paula Chanfreut, Twan Keijzer, Riccardo M. G. Ferrari, Jose Maria Maestre:
A Topology-Switching Coalitional Control and Observation Scheme with Stability Guarantees. CoRR abs/2104.03787 (2021)
2010 – 2019
- 2019
- [c2]Paula Chanfreut, José María Maestre, Francisco Javier Muros
, Eduardo F. Camacho:
A Coalitional Control Scheme with Topology-Switchings Convexity Guarantees. CDC 2019: 1096-1101 - 2018
- [c1]Paula Chanfreut, José María Maestre, Hideaki Ishii:
Vulnerabilities in Distributed Model Predictive Control based on Jacobi-Gauss Decomposition. ECC 2018: 2587-2592
Coauthor Index
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