Journal papers

2023

T R V Steentjes, M Lazar, P M J Van den Hof: On a canonical distributed controller in the behavioral framework. Systems & Control Letters, 179 (105581), 2023. (Type: Journal Article | Links)
E E M Kivits, P M J Van den Hof: Identification of diffusively coupled linear networks through structured polynomial models. IEEE Trans. Automatic Control, 68 (6), pp. 3513-3528, 2023. (Type: Journal Article | Links)
S Shi, X Cheng, P M J Van den Hof: Single module identifiability in linear dynamic networks with partial excitation and measurement. IEEE Trans. Automatic Control, 68 (1), pp. 285-300, 2023. (Type: Journal Article | Links)
X Bombois, K Colin, P M J Van den Hof, H Hjalmarsson: On the informativity of direct identification experiments in dynamical networks. Automatica, 148 (110742), 2023. (Type: Journal Article | Links)
X Cheng, S Shi, I Lestas, P M J Van den Hof: A necessary condition for network identifiability with partial excitation and measurement. IEEE Trans. Automatic Control, 68 (11), pp. 6820-6827, 2023. (Type: Journal Article | Links)
Control Systems Group, Eindhoven University of Technology : SYSDYNET Toolbox for MATLAB, Version Beta 0.2.0. 2023. (Type: Journal Article | Links)
P M J Van den Hof, K R Ramaswamy, S J M Fonken: Integrating data-informativity conditions in predictor models for single module identification in dynamic networks. IFAC-PapersOnLine, 56-2 , pp. 2377-2382, 2023, (Proc. 22nd IFAC World Congress, 9-14 July, 2023, Yokohama, Japan). (Type: Journal Article | Links)
S Shi, X Cheng, B De Schutter, P M J Van den Hof: Signal selection for local module identification in linear dynamic networks: A graphical approach. IFAC-PapersOnLine, 56-2 , pp. 2407-2412, 2023, (Proc. 22nd IFAC World Congress, 9-14 July, 2023, Yokohama, Japan). (Type: Journal Article | Links)
E M M Kivits, P M J Van den Hof: Identifiability of diffusively coupled linear networks with partial instrumentation. IFAC-PapersOnLine, 56-2 , pp. 2395-2400, 2023, (Proc. 22nd IFAC World Congress, 9-14 July, 2023, Yokohama, Japan). (Type: Journal Article | Links)

2022

K R Ramaswamy, P Z Csurcsia, J Schoukens, P M J Van den Hof: A frequency domain approach for local module identification in dynamic networks. Automatica, 142 (110370), 2022. (Type: Journal Article | Links)
S J M Fonken, K R Ramaswamy, P M J Van den Hof: A scalable multi-step least squares method for network identification with unknown disturbance topology. Automatica, 141 (110295), 2022. (Type: Journal Article | Links)
S Shi, X Cheng, P M J Van den Hof: Generic identifiability of subnetworks in a linear dynamic network: the full measurement case. Automatica, 137 (110093), 2022. (Type: Journal Article | Links)
X Cheng, S Shi, P M J Van den Hof: Allocation of excitation signals for generic identifiability of linear dynamic networks. IEEE Trans. Automatic Control, 67 (2), pp. 592-705, 2022. (Type: Journal Article | Links)
T M V Steentjes, M Lazar, P M J Van den Hof: On data-driven control: informativity of noisy input-output data with cross-covariance bounds. IEEE Control Systems Letters (L-CSS), 6 , pp. 2192-2197, 2022. (Type: Journal Article | Links)
H J Dreef, S Shi, X. Cheng, M C F Donkers, P M J Van den Hof: Excitation allocation for generic identifiability of linear dynamic networks with fixed modules. IEEE Control Systems Letters (L-CSS), 6 , pp. 2587-2592, 2022. (Type: Journal Article | Links)

2021

K R Ramaswamy, P M J Van den Hof: A local direct method for module identification in dynamic networks with correlated noise. IEEE Trans. Automatic Control, 66 (11), pp. 5237-5252, 2021. (Type: Journal Article | Links)
K R Ramaswamy, G Bottegal, P M J Van den Hof: Learning linear models in a dynamic network using regularized kernel-based methods. Automatica, 129 (109591), 2021. (Type: Journal Article | Links)
T R V Steentjes, M Lazar, P M J Van den Hof: Scalable distributed H2 controller synthesis for interconnected linear discrete-time systems. IFAC-PapersOnLine, 54-9 , pp. 66-71, 2021, (Proc. 24th Intern. Symposium MTNS, Cambridge, UK). (Type: Journal Article | Links)
H J Dreef, M C F Donkers, P M J Van den Hof: Identifiability of linear dynamic networks through switching modules. IFAC-PapersOnLine, 54-7 , pp. 37-42, 2021, (Proc. 19th IFAC Symposium on System Identification - Learning Models for Decision and Control). (Type: Journal Article | Links)
T R V Steentjes, P M J Van den Hof, M Lazar: Handling unmeasured disturbances in data-driven distributed control with virtual reference feedback tuning. IFAC-PapersOnLine, 54-7 , pp. 204-209, 2021, (Proc. 19th IFAC Symposium on System Identification - Learning Models for Decision and Control). (Type: Journal Article | Links)
P M J Van den Hof, K R Ramaswamy: Learning local models in dynamic networks. Proc. Machine Learning Research, 144 , pp. 176-188, 2021. (Type: Journal Article | Links)

2020

R J C van Esch, S Shi, A Bernas, Zinger Z., A P Aldenkamp, P M J Van den Hof: A Bayesian method for inference of effective connectivity in brain networks for detecting the Mozart effect. Computers in Biology and Medicine, 2020. (Type: Journal Article | Links)
H H M Weerts, J Linder, M Enqvist, P M J Van den Hof: Abstractions of linear dynamic networks for input selection in local module identification. Automatica, 117 (108975), 2020. (Type: Journal Article | Links)
S Shi, X Cheng, P M J Van den Hof: Excitation allocation for generic identifiability of a single module in dynamic networks: A graphic approach. IFAC-PapersOnLine, 53-2 , pp. 40-45, 2020, (Proc. 21st IFAC World Congress, Berlin, Germany). (Type: Journal Article | Links)
S Fonken, M Ferizbegovic, H Hjalmarsson: Consistent identification of dynamic networks subject to white noise using weighted null-space fitting. IFAC-PapersOnLine, 53-2 , pp. 46-51, 2020, (Proc. 21st IFAC World Congress, Berlin, Germany). (Type: Journal Article | Links)

2018

H H M Weerts, P M J Van den Hof, A G Dankers: Prediction error identification of linear dynamic networks with rank-reduced noise. Automatica, 98 , pp. 256-268, 2018. (Type: Journal Article | Links)
N Everitt, G Bottegal, H Hjalmarsson: An emperical Bayes approach to identification of modules in dynamic networks. Automatica, 91 , pp. 144-151, 2018. (Type: Journal Article | Links)
H H M Weerts, P M J Van den Hof, A G Dankers: Identifiability of linear dynamic networks. Automatica, 89 , pp. 247-258, 2018. (Type: Journal Article | Links)
P M J Van den Hof, A G Dankers, Weerts H H M: Identification in dynamic networks. Computers & Chemical Engineering, 109 , pp. 23-29, 2018. (Type: Journal Article | Links)
H H M Weerts, M Galrinho, G Bottegal, H Hjalmarsson, P M J Van den Hof: A sequential least squares algorithm for ARMAX dynamic network identification. IFAC-PapersOnLine, 51-15 , pp. 844-849, 2018, (Proc. 18th IFAC Symp. System Identification). (Type: Journal Article | Links)
G Bottegal, A Chiuso, P M J Van den Hof: On dynamic network modeling of stationary multivariate processes. IFAC-PapersOnLine, 51-15 , pp. 850-861, 2018, (Proc. 18th IFAC Symp. System Identification). (Type: Journal Article | Links)
E M M Kivits, P M J Van den Hof: On representations of linear dynamic networks. IFAC-PapersOnLine, 51-15 , pp. 838-843, 2018, (Proc. 18th IFAC Symp. System Identification). (Type: Journal Article | Links)
M Schoukens, P M J Van den Hof: Detecting nonlinear modules in a dynamic network: a step-by-step procedure. IFAC-PapersOnLine, 51-15 , pp. 593-597, 2018, (Proc. 18th IFAC Symp. System Identification). (Type: Journal Article | Links)
T R V Steentjes, M Lazar, P M J Van den Hof: A recursive estimation approach to distributed identification of large-scale multi-input single output FIR systems. IFAC-PapersOnLine, 51-23 , pp. 236-241, 2018, (Proc. 7th IFAC Workshop on Distributed Estimation and Control in Networked Systems). (Type: Journal Article | Links)

2017

H H M Weerts, P M J Van den Hof, A G Dankers: Identification of dynamic networks with rank-reduced process noise. IFAC-PapersOnLine, 50-1 , pp. 10562-10567, 2017, (Proc. 20th IFAC World Congress). (Type: Journal Article | Links)
A G Dankers, P M J Van den Hof, D Materassi, H H M Weerts: Conditions for handling confounding variables in dynamic networks. IFAC-PapersOnLine, 50-1 , pp. 3983-3988, 2017, (Proc. 20th IFAC World Congress). (Type: Journal Article | Links)

2016

A G Dankers, P M J Van den Hof, P S C Heuberger, X Bombois: Identification of Dynamic Models in Complex Networks With Prediction Error Methods: Predictor Input Selection. IEEE Trans. on Automatic Control, 61 (4), pp. 937–952, 2016. (Type: Journal Article | Links)
H H M Weerts, P M J Van den Hof, A G Dankers: Identifiability of dynamic networks with part of the nodes noise-free. IFAC-PapersOnLine, 49 (13), pp. 19-24, 2016, (Proc. 12th IFAC Workshop ALCOSP, Eindhoven, the Netherlands.). (Type: Journal Article | Links)

2015

A G Dankers, P M J Van den Hof, X Bombois, P S C Heuberger: Errors-in-variables identification in dynamic networks mbox-- Consistency results for an instrumental variable approach. Automatica, 62 , pp. 39–50, 2015. (Type: Journal Article | Links)
H H M Weerts, A G Dankers, P M J Van den Hof: Identifiability in dynamic network identification. IFAC-PapersOnLine, 48-28 , pp. 1409–1414, 2015, (Proc. 17th IFAC Symposium on System Identification, Beijing, China). (Type: Journal Article | Links)

2013

P M J Van den Hof, A G Dankers, P S C Heuberger, X Bombois: Identification of dynamic models in complex networks with prediction error methods - basic methods for consistent module estimates. Automatica, 49 (10), pp. 2994–3006, 2013. (Type: Journal Article | Links)