Data-driven Modelling in Dynamic Networks

Project Information

SYSDYNET

Grant agreement ID: 694504

DOI 10.3030/694504

Project closed

EC signature date 13 May 2016

Start date 1 September 2016

End date 31 August 2022

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost € 2 499 690,00

EU contribution € 2 499 690,00

Coordinated by

TECHNISCHE UNIVERSITEIT EINDHOVEN
Netherlands

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Peer reviewed articles (30)

A local direct method for module identification in dynamic networks with correlated noise

Author(s): Karthik R. Ramaswamy, Paul M.J. Vandenhof
Published in: IEEE Transactions on Automatic Control, 2019, Page(s) 1-1, ISSN 0018-9286
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tac.2020.3035634

Identification of diffusively coupled linear networks through structured polynomial models

Author(s): E.M.M. Kivits, Paul M.J. Van den Hof
Published in: IEEE Transactions on Automatic Control, Issue 00189286, 2023, ISSN 0018-9286
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tac.2022.3191406

Excitation allocation for generic identifiability of a single module in dynamic networks: A graphic approach

Author(s): Shengling Shi, Xiaodong Cheng, Paul M.J. Van den Hof
Published in: IFAC-PapersOnLine, Issue 53/2, 2020, Page(s) 40-45, ISSN 2405-8963
Publisher: IFAC
DOI: 10.1016/j.ifacol.2020.12.042

A frequency domain approach for local module identification in dynamic networks

Author(s): Karthik Raghavan Ramaswamy, Péter Zoltán Csurcsia, Johan Schoukens, Paul M.J.Van den Hof
Published in: Automatica, Issue 00051098, 2022, ISSN 0005-1098
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2022.110370

A Bayesian method for inference of effective connectivity in brain networks for detecting the Mozart effect

Author(s): Rik J.C. van Esch, Shengling Shi, Antoine Bernas, Svitlana Zinger, Albert P. Aldenkamp, Paul M.J. Van den Hof
Published in: Computers in Biology and Medicine, Issue 127, 2020, Page(s) 104055, ISSN 0010-4825
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.compbiomed.2020.104055

Generic identifiability of subnetworks in a linear dynamic network: The full measurement case

Author(s): Shengling Shi, Xiaodong Cheng, Paul M.J. Van den Hof
Published in: Automatica, Issue 00051098, 2022, ISSN 0005-1098
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2021.110093

On Data-Driven Control: Informativity of Noisy Input-Output Data With Cross-Covariance Bounds

Author(s): Tom R. V. Steentjes, Mircea Lazar, Paul M. J. Van den Hof
Published in: IEEE Control Systems Letters, Issue 24751456, 2022, Page(s) 2192 - 2197, ISSN 2475-1456
Publisher: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/lcsys.2021.3139526

Identifiability of linear dynamic networks through switching modules

Author(s): H.J. Dreef, M.C.F. Donkers, Paul M.J. Van den Hof
Published in: IFAC-PapersOnLine, Issue 24058963, 2021, Page(s) 37-42, ISSN 2405-8963
Publisher: Elsevier B.V.
DOI: 10.1016/j.ifacol.2021.08.331

Scalable distributed H2 controller synthesis for interconnected linear discrete-time systems

Author(s): Tom R.V. Steentjes, Mircea Lazar, Paul M.J. Van den Hof
Published in: IFAC-PapersOnLine, Issue 24058963, 2021, Page(s) 66-71, ISSN 2405-8963
Publisher: Elsevier B.V.
DOI: 10.1016/j.ifacol.2021.06.178

Learning linear modules in a dynamic network with missing node observations

Author(s): Karthik R. Ramaswamy, Giulio Bottegal, Paul M.J. Van den Hof
Published in: Automatica, Issue 00051098, 2022, Page(s) 1-16, ISSN 0005-1098
Publisher: Pergamon Press Ltd.
DOI: 10.48550/arxiv.2208.10995

Single module identifiability in linear dynamic networks with partial excitation and measurement

Author(s): Shengling Shi, Xiaodong Cheng, Paul M.J. Van den Hof
Published in: IEEE Transactions Automatic Control, Issue 00189286, 2023, ISSN 0018-9286
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tac.2021.3137787

Allocation of Excitation Signals for Generic Identifiability of Linear Dynamic Networks

Author(s): Xiaodong Cheng, Shengling Shi, Paul M.J. Van den Hof
Published in: IEEE Transactions on Automatic Control, 2019, Page(s) 1-1, ISSN 0018-9286
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tac.2021.3053540

Excitation Allocation for Generic Identifiability of Linear Dynamic Networks With Fixed Modules

Author(s): H.J. Dreef, Shengling Shi, Xiaodong Cheng, M.C.F. Donkers, Paul M.J. Van den Hof
Published in: IEEE Control Systems Letters, Issue 24751456, 2022, Page(s) 2587-2592, ISSN 2475-1456
Publisher: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/lcsys.2022.3171172

Learning linear modules in a dynamic network using regularized kernel-based methods

Author(s): Karthik Raghavan Ramaswamy, Giulio Bottegal, Paul M.J. Van den Hof
Published in: Automatica, Issue 129, 2021, Page(s) 109591, ISSN 0005-1098
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2021.109591

Handling unmeasured disturbances in data-driven distributed control with virtual reference feedback tuning

Author(s): Tom R.V. Steentjes, Paul M.J. Van den Hof, Mircea Lazar
Published in: IFAC-PapersOnLine, Issue 24058963, 2021, Page(s) 204-209, ISSN 2405-8963
Publisher: Elsevier B.V.
DOI: 10.1016/j.ifacol.2021.08.359

Consistent identification of dynamic networks subject to white noise using Weighted Null-Space Fitting

Author(s): Stefanie Fonken, Mina Ferizbegovic, Håkan Hjalmarsson
Published in: IFAC-PapersOnLine, Issue 53/2, 2020, Page(s) 46-51, ISSN 2405-8963
Publisher: IFAC
DOI: 10.1016/j.ifacol.2020.12.047

Identification in dynamic networks

Author(s): Paul M.J. Van den Hof, Arne G. Dankers, Harm H.M. Weerts
Published in: Computers & Chemical Engineering, Issue 109, 2018, Page(s) 23-29, ISSN 0098-1354
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.compchemeng.2017.10.005

Identifiability of linear dynamic networks

Author(s): Harm H.M. Weerts, Paul M.J. Van den Hof, Arne G. Dankers
Published in: Automatica, Issue 89, 2018, Page(s) 247-258, ISSN 0005-1098
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2017.12.013

Conditions for handling confounding variables in dynamic networks * *The work of A. Dankers is supported by Mitacs of Canada. The work of P. Van den Hof and H. Weerts is supported by the European Research Council (ERC), Advanced Research Grant SYSDYNET, under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 694504).

Author(s): Arne Dankers, Paul M.J. Van den Hof, Donatello Materassi, Harm H.M. Weerts
Published in: IFAC-PapersOnLine, Issue 50/1, 2017, Page(s) 3983-3988, ISSN 2405-8963
Publisher: Elsevier
DOI: 10.1016/j.ifacol.2017.08.771

Detecting Nonlinear Modules in a Dynamic Network: A Step-by-Step Procedure

Author(s): M. Schoukens, P.M.J. Van den Hof
Published in: IFAC-PapersOnLine, Issue 51/15, 2018, Page(s) 593-597, ISSN 2405-8963
Publisher: Elsevier
DOI: 10.1016/j.ifacol.2018.09.224

An empirical Bayes approach to identification of modules in dynamic networks

Author(s): Niklas Everitt, Giulio Bottegal, Håkan Hjalmarsson
Published in: Automatica, Issue 91, 2018, Page(s) 144-151, ISSN 0005-1098
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2018.01.011

A sequential least squares algorithm for ARMAX dynamic network identification

Author(s): Harm H.M. Weerts, Miguel Galrinho, Giulio Bottegal, Håkan Hjalmarsson, Paul M.J. Van den Hof
Published in: IFAC-PapersOnLine, Issue 51/15, 2018, Page(s) 844-849, ISSN 2405-8963
Publisher: Elsevier
DOI: 10.1016/j.ifacol.2018.09.119

Combining Experiments for Linear Dynamic Network Identification in the Presence of Nonlinearities

Author(s): M. Schoukens, J.P. Noël, P.M.J. Van den Hof
Published in: Journal of Physics: Conference Series, Issue 1065, 2018, Page(s) 212026, ISSN 1742-6588
Publisher: Institute of Physics
DOI: 10.1088/1742-6596/1065/21/212026

Prediction error identification of linear dynamic networks with rank-reduced noise

Author(s): Harm H.M. Weerts, Paul M.J. Van den Hof, Arne G. Dankers
Published in: Automatica, Issue 98, 2018, Page(s) 256-268, ISSN 0005-1098
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2018.09.033

A recursive estimation approach to distributed identification of large-scale multi-input-single-output FIR systems

Author(s): Tom R.V. Steentjes, Mircea Lazar, Paul M.J. Van den Hof
Published in: IFAC-PapersOnLine, Issue 51/23, 2018, Page(s) 236-241, ISSN 2405-8963
Publisher: Elsevier
DOI: 10.1016/j.ifacol.2018.12.041

On dynamic network modeling of stationary multivariate processes

Author(s): Giulio Bottegal, Alessandro Chiuso, Paul M.J. Van den Hof
Published in: IFAC-PapersOnLine, Issue 51/15, 2018, Page(s) 850-855, ISSN 2405-8963
Publisher: Elsevier
DOI: 10.1016/j.ifacol.2018.09.118

On Representations of Linear Dynamic Networks

Author(s): E.M.M. Kivits, Paul M.J. Van den Hof
Published in: IFAC-PapersOnLine, Issue 51/15, 2018, Page(s) 838-843, ISSN 2405-8963
Publisher: Elsevier
DOI: 10.1016/j.ifacol.2018.09.120

Identification of dynamic networks with rank-reduced process noise * *This work has received funding from the European Research Council (ERC), Advanced Research Grant SYSDYNET, under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 694504).

Author(s): Harm H.M. Weerts, Paul M.J. Van den Hof, Arne G. Dankers
Published in: IFAC-PapersOnLine, Issue 50/1, 2017, Page(s) 10562-10567, ISSN 2405-8963
Publisher: Elsevier
DOI: 10.1016/j.ifacol.2017.08.1319

A scalable multi-step least squares method for network identification with unknown disturbance topology

Author(s): Stefanie J.M.Fonken, Karthik Raghavan Ramaswamy, Paul M.J.Van den Hof
Published in: Automatica, Issue 00051098, 2022, ISSN 0005-1098
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2022.110295

Abstractions of linear dynamic networks for input selection in local module identification

Author(s): Harm H.M. Weerts, Jonas Linder, Martin Enqvist, Paul M.J. Van den Hof
Published in: Automatica, Issue 117, 2020, Page(s) 108975, ISSN 0005-1098
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2020.108975

Thesis and dissertations (14)

Identifiability and identification methods for dynamic networks

Author(s): H H M Weerts
Published in: PhD Thesis, 2018
Publisher: Eindhoven University of Technology

Learning local modules in dynamic networks without prior topology information

Author(s): V. Comandoor Rajagopal
Published in: Master Thesis, 2020
Publisher: Eindhoven University of Technology

Topology detection in brain networks

Author(s): R. van Esch
Published in: Master thesis, 2019
Publisher: Eindhoven University of Technology

System Identification of the Inertia and Natural Damping of an Interconnected control Area

Author(s): B.J.T. Ludlage
Published in: Master thesis, 2017
Publisher: Eindhoven University of Technology

Topology detection using Bayesian statistics

Author(s): Răclaru Eduard-Edis
Published in: Master thesis, 2018
Publisher: Eindhoven Unioversity of Technology

Improvements for In-Circuit Testing using RLC Network Identification

Author(s): J.B.T. Meijer
Published in: Master thesis, 2021
Publisher: Eindhoven University of Technology

Data-driven methods for distributed control of interconnected linear systems

Author(s): Tom Robert Vince Steentjes
Published in: PhD thesis, 2022, ISBN 978-90-386-5528-4
Publisher: Eindhoven University of Technology

An iterative algorithm for learning dynamic networks with correlated noise

Author(s): V. C. Rajagopal
Published in: MSc internship report, 2019
Publisher: Eindhoven University of Technology

Multi-step scalable least squares method for network identification with unknown noise topology

Author(s): S.J.M. Fonken
Published in: Master Thesis, 2020
Publisher: Eindhoven University of Technology

Topological aspects of linear dynamic networks: identifiability and identification

Author(s): Shengling Shi
Published in: PhD thesis, 2021, ISBN 978-90-386-5324-2
Publisher: Eindhoven University of Technology

Identification of Continuous-time ARX-Models Subject to Missing Data

Author(s): Yang Song
Published in: Master Thesis, 2018
Publisher: Eindhoven University of Technology

Data-driven modelling and decentralized H2 control of power networks

Author(s): Anupama
Published in: Master thesis, 2021
Publisher: Eindhoven University of Technology

Centralized and distributed identified model based predictive control for Museum Hermitage Amsterdam

Author(s): X. Chen
Published in: Master Thesis, 2019
Publisher: Eindhoven University of Technology

A guide to learning modules in a dynamic network

Author(s): Karthik Raghavan Ramaswamy
Published in: PhD thesis, 2022, ISBN 978-90-386-5500-0
Publisher: Eindhoven University of Technology

Conference proceedings (19)

Learning local modules in dynamic networks without prior topology information

Author(s): Venkatakrishnan C. Rajagopal, Karthik R. Ramaswamy, Paul M.J. Van Den Hof
Published in: 2021 60th IEEE Conference on Decision and Control (CDC), 2022, Page(s) 840-845, ISBN 978-1-6654-3659-5
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/cdc45484.2021.9683377

Allocation of Excitation Signals for Generic Identifiability of Dynamic Networks

Author(s): Xiaodong Cheng, Shengling Shi, Paul M.J. Van den Hof
Published in: 2019 IEEE 58th Conference on Decision and Control (CDC), 2019
Publisher: IEEE
DOI: 10.1109/cdc40024.2019.9029218

H_infinity performance analysis an distributed controller synthesis for interconnected linear systems from noisy input-state data

Author(s): Tom R.V. Steentjes, Mircea Lazar, Paul M.J. Van den Hof
Published in: 60th IEEE Conference on Decision and Control (CDC 2021), 2022, Page(s) 3723-3728, ISBN 978-1-6654-3659-5
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/cdc45484.2021.9683126

Learning local modules in dynamic networks

Author(s): Paul M.J. Van den Hof, Karthik R. Ramaswamy
Published in: Proceedings of Machine Learning Research, Issue 26403498, 2021, Page(s) 176-188, ISSN 2640-3498
Publisher: Proceedings of Machine Learning Research

Identifiability in Dynamic Acyclic Networks with Partial Excitation and Measurement

Author(s): Xiaodong Cheng, Shengling Shi, Ioannis Lestas, Paul M. J. Van den Hof
Published in: 2021 European Control Conference, 2021
Publisher: IEEE
DOI: 10.48550/arxiv.2201.07548

A dynamic network approach to identification of physical systems

Author(s): E.M.M. Lizan Kivits, Paul M.J. Van den Hof
Published in: 2019 IEEE 58th Conference on Decision and Control (CDC), 2019, Page(s) 4533-4538, ISBN 978-1-7281-1398-2
Publisher: IEEE
DOI: 10.1109/cdc40024.2019.9030041

Data-driven distributed controller synthesis in the presence of noise: an optimal controller identification approach

Author(s): T R V Steentjes, M Lazar, P M J Van den Hof
Published in: 2021 European Control Conference, 2021
Publisher: IEEE
DOI: 10.23919/ecc54610.2021.9655114

Path-based data-informativity conditions for single module identification in dynamic networks

Author(s): Paul M.J. Van den Hof, Karthik R. Ramaswamy
Published in: 2020 59th IEEE Conference on Decision and Control (CDC), 2020, Page(s) 4354-4359, ISBN 978-1-7281-7447-1
Publisher: IEEE
DOI: 10.1109/cdc42340.2020.9304263

A regularized kernel-based method for learning a module in a dynamic network with correlated noise

Author(s): Venkatakrishnan C. Rajagopal, Karthik R. Ramaswamy, Paul M.J. Van den Hof
Published in: 2020 59th IEEE Conference on Decision and Control (CDC), 2020, Page(s) 4348-4353, ISBN 978-1-7281-7447-1
Publisher: IEEE
DOI: 10.1109/cdc42340.2020.9303879

Generalized sensing and actuation schemes for local module identification in dynamic networks

Author(s): Karthik R. Ramaswamy, Paul M. J. Van den Hof, Arne G. Dankers
Published in: 2019 IEEE 58th Conference on Decision and Control (CDC), 2019, Page(s) 5519-5524, ISBN 978-1-7281-1398-2
Publisher: IEEE
DOI: 10.1109/cdc40024.2019.9029338

From closed-loop identification to dynamic networks: Generalization of the direct method

Author(s): Paul M.J. Van den Hof, Arne G. Dankers, Harm H.M. Weerts
Published in: 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 2017, Page(s) 5845-5850, ISBN 978-1-5090-2873-3
Publisher: IEEE
DOI: 10.1109/cdc.2017.8264543

Prediction error identification with rank-reduced output noise

Author(s): Paul M.J. Van den Hof, Harm H.M. Weerts, Arne G. Dankers
Published in: 2017 American Control Conference (ACC), 2017, Page(s) 382-387, ISBN 978-1-5090-5992-8
Publisher: IEEE
DOI: 10.23919/acc.2017.7962983

Identification in dynamic networks

Author(s): P.M.J Van den Hof, A.G. Dankers, H.H.M. Weerts
Published in: Proc. Foundations of Computer Aided Process Operations / Chemical Process Control FOCAPO/CPC 2017, 2017
Publisher: FOCAPO/CPC 2017

Single Module Identifiability in Linear Dynamic Networks

Author(s): Harm Weerts, Paul M.J. Van den Hof, Arne Dankers
Published in: 2018 IEEE Conference on Decision and Control (CDC), 2018, Page(s) 4725-4730, ISBN 978-1-5386-1395-5
Publisher: IEEE
DOI: 10.1109/cdc.2018.8619365

Local Module Identification in Dynamic Networks Using Regularized Kernel-Based Methods

Author(s): Karthik R. Ramaswamy, Giulio Bottegal, Paul M.J. Van den Hof
Published in: 2018 IEEE Conference on Decision and Control (CDC), 2018, Page(s) 4713-4718, ISBN 978-1-5386-1395-5
Publisher: IEEE
DOI: 10.1109/cdc.2018.8619436

Bayesian topology identification of linear dynamic networks

Author(s): Shengling Shi, Giulio Bottegal, Paul M. J. Van den Hof
Published in: 2019 18th European Control Conference (ECC), 2019, Page(s) 2814-2819, ISBN 978-3-907144-00-8
Publisher: IEEE
DOI: 10.23919/ecc.2019.8795766

Informativity conditions for data-driven control based on input-state data and polyhedral cross-covariance noise bounds

Author(s): T R V Steentjes, M Lazar, P M J Van den Hof
Published in: International Symposium on Mathematical Theory of Networks and Systems, 2022, Page(s) 816-821
Publisher: MTNS
DOI: 10.48550/arxiv.2202.09266

Data-driven distributed control: Virtual reference feedback tuning in dynamic networks

Author(s): Tom R.V. Steentjes, Mircea Lazar, Paul M.J. Van den Hof
Published in: 2020 59th IEEE Conference on Decision and Control (CDC), 2020, Page(s) 1804-1809, ISBN 978-1-7281-7447-1
Publisher: IEEE
DOI: 10.1109/cdc42340.2020.9304099

Local module identification in dynamic networks with correlated noise: the full input case

Author(s): Paul M.J. Van den Hof, Karthik R. Ramaswamy, Arne G. Dankers, Giulio Bottegal
Published in: 2019 IEEE 58th Conference on Decision and Control (CDC), 2019, Page(s) 5494-5499, ISBN 978-1-7281-1398-2
Publisher: IEEE
DOI: 10.1109/cdc40024.2019.9029448

Other (3)

Bayesian topology identification of linear dynamic networks

Author(s): Shengling Shi, Giulio Bottegal, Paul M. J. Van den Hof
Published in: Technical Report, 2018
Publisher: Eindhoven University of Technology

Abstractions of linear dynamic networks for input selection in local module identification

Author(s): Weerts, Harm H. M.; Linder, Jonas; Enqvist, Martin; Hof, Paul M. J. Van den
Published in: Technical report, Issue 2, 2019
Publisher: Eindhoven University of Technology

Scalable distributed and decentralized H2 controller synthesis for interconnected linear discrete-time systems

Author(s): Tom R. V. Steentjes, Mircea Lazar, Paul M. J. Van den Hof
Published in: Technical report, 2019
Publisher: Eindhoven University of Technology