Conference papers

2024
Y Shi, S J M Fonken, P M J Van den Hof: Fault detection and diagnosis using the dynamic network framework. Proc. 20th IFAC Symp. System Identification, 17-18 July 2024, Boston, MA, USA, pp. 395-400, Boston, 2024. (Type: Inproceedings | Links)
P M J Van den Hof, S Shi, H H M Weerts, X Cheng, K R Ramaswamy, A G Dankers, H J DReef, S J M Fonken, T R V Steentjes, J B T Meijer: SYSDYNET - A MATLAB app and toolbox for dynamic network identification. Proc. 20th IFAC Symp. System Identification, 17-18 July 2024, Boston, MA, USA, pp. 585-590, Boston, 2024. (Type: Inproceedings | Links)

2023
S J M Fonken, K R Ramaswamy, P M J Van den Hof: Local identification in dynamic networks using a multi-step least squares method. Proc. 62th IEEE Conf. on Decision and Control (CDC), pp. 431-436, IEEE Singapore, 2023. (Type: Inproceedings | Links)

2022
T R V Steentjes, M Lazar, P M J Van den Hof: Informativity conditions for data-driven control based on input-state data and polyhedral cross-covariance noise bounds. Proc. 25th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2022), pp. 816-821, Bayreuth, Germany, 2022. (Type: Inproceedings | Links)
E M M Kivits, P M J Van den Hof: Local identification in diffusively coupled linear networks. Proc. 61th IEEE Conf. on Decision and Control (CDC), pp. 874-879, IEEE Cancun, Mexico, 2022. (Type: Inproceedings | Links)

2021
T R V Steentjes, M Lazar, P M J Van den Hof: H_infinity performance analysis an distributed controller synthesis for interconnected linear systems from noisy input-state data. Proc. 60th IEEE Conf. on Decision and Control (CDC), pp. 3723-3728, IEEE Austin, Texas, 2021. (Type: Inproceedings | Links)
V C Rajagopal, K R Ramaswamy, P M J Van den Hof: Learning local modules in dynamic networks without prior topology information. Proc. 60th IEEE Conf. on Decision and Control (CDC), pp. 840-845, IEEE Austin, Texas, 2021. (Type: Inproceedings | Links)
S Shi, X Cheng, P M J Van den Hof: Exploiting unmeasured disturbance signals in identifiability of linear dynamic networks with partial measurement and partial excitation. Prepr. 19th IFAC Symposium on System Identification - Learning Models for Decision and Control, pp. 264-267, Padova, Italy, 2021, (Extended abstract). (Type: Inproceedings | Links)
X Cheng, S Shi, P M J Van den Hof: Identifiability in dynamic acyclic networks with partial excitation and measurement. Prepr. 2021 European Control Conference, IEEE Rotterdam, The Netherlands, 2021, (Extended abstract). (Type: Conference | Links)
T R V Steentjes, M Lazar, P M J Van den Hof: Data-driven distributed controller synthesis in the presence of noise: an optimal controller identification approach. Proc. 2021 European Control Conference, pp. 2358-2363, IEEE Rotterdam, The Netherlands, 2021. (Type: Inproceedings | Links)

2020
P M J Van den Hof, K R Ramaswamy: Single module identification in dynamic networks - the current status. Prepr. 21st IFAC World Congress, pp. 52-55, Berlin, Germany, 2020, (Extended abstract). (Type: Inproceedings | Links)
P M J Van den Hof, K R Ramaswamy: Path-based data-informativity conditions for single module identification in dynamic networks. Proc. 59th IEEE Conf. on Decision and Control (CDC), pp. 4354-4359, IEEE Jeju Island, Republic of Korea, 2020. (Type: Inproceedings | Links)
T R V Steentjes, M Lazar, P M J Van den Hof: Data-driven distributed control via virtual reference feedback tuning. Proc. 59th IEEE Conf. on Decision and Control (CDC), pp. 1804-1809, IEEE Jeju Island, Republic of Korea, 2020. (Type: Inproceedings | Links)
V C Rajagopal, K R Ramaswamy, P M J Van den Hof: A regularized kernel-based method for learning a module in a dynamic network with correlated noise. Proc. 59th IEEE Conf. on Decision and Control (CDC), pp. 4348-4353, IEEE Jeju Island, Republic of Korea, 2020. (Type: Inproceedings | Links)

2019
S Shi, G Bottegal, P M J Van den Hof: Bayesian topology identification of linear dynamic networks. Proc. 2019 European Control Conference, pp. 2814-2819, Napels, Italy, 2019. (Type: Inproceedings | Links)
K R Ramaswamy, P M J Van den Hof, Dankers A G.: Generalized sensing and actuation schemes for local module identification in dynamic networks. Proc. 58th IEEE Conf. on Decision and Control (CDC), pp. 5519-5524, IEEE Nice, France, 2019. (Type: Inproceedings | Links)
P M J Van den Hof, K R Ramaswamy, A G Dankers, G Bottegal: Local module identification in dynamic networks with correlated noise: the full input case. Proc. 58th IEEE Conf. on Decision and Control (CDC), pp. 5494-5499, IEEE Nice, France, 2019. (Type: Inproceedings | Links)
X Cheng, S Shi, P M J Van den Hof: Allocation of excitation signals for generic identifiability of dynamic networks. Proc. 58th IEEE Conf. on Decision and Control (CDC), pp. 5507-5512, IEEE Nice, France, 2019. (Type: Inproceedings | Links)
E M M Kivits, P M J Van den Hof: A dynamic network approach to identification of physical systems. Proc. 58th IEEE Conf. on Decision and Control (CDC), pp. 4533-4538, IEEE Nice, France, 2019. (Type: Inproceedings | Links)

2018
M Schoukens, J P Noël, P M J Van den Hof: Combining experiments for linear network identification in the presence of nonlinearities.. Journal of Physics: Conference Series, 2018, (Proc. XXII World Congress of the International Measurement Confederation (IMEKO 2018), Belfast, UK). (Type: Inproceedings | Links)
H H M Weerts, P M J Van den Hof, A G Dankers: Single module identifiability in linear dynamic networks. Proc. 57th IEEE Conf. on Decision and Control (CDC), pp. 4725-4730, IEEE Miami Beach, FL, 2018. (Type: Inproceedings | Links)
K R Ramaswamy, G Bottegal, P M J Van den Hof: Local module identification in dynamic networks using regularized kernel-based methods. Proc. 57th IEEE Conf. on Decision and Control (CDC), pp. 4713-4718, IEEE Miami Beach, FL, 2018. (Type: Inproceedings | Links)

2017
P M J Van den Hof, A G Dankers, H H M Weerts: Identification in dynamic networks. Proc. Foundations of Computer Aided Process Operations / Chemical Process Control (FOCAPO/CPC 2017), Tucson, AZ, USA, 2017. (Type: Inproceedings | Links)
P M J Van den Hof, H H M Weerts, A G Dankers: Prediction error identification with rank-reduced output noise. Proc. 2017 American Control Conference, pp. 382–387, Seattle, 2017. (Type: Inproceedings | Links)
P M J Van den Hof, A G Dankers, H H M Weerts: From closed-loop identification to dynamic networks: generalization of the direct method. Proc. 56th IEEE Conf. on Decision and Control (CDC), pp. 5845-5850, IEEE Melbourne, Australia, 2017. (Type: Inproceedings | Links)

2016
H H M Weerts, P M J Van den Hof, A G Dankers: Identification of dynamic networks operating in the presence of algebraic loops. Proc. 55nd IEEE Conf. on Decision and Control (CDC), pp. 4606–4611, IEEE 2016. (Type: Inproceedings | Links)

2015
A G Dankers, P M J Van den Hof: Non-parametric identification in dynamic networks. Proc. 54th IEEE Conf. on Decision and Control (CDC), pp. 3487-3492, IEEE Osaka, Japan, 2015. (Type: Inproceedings | Links)

2014
A G Dankers, P M J Van den Hof, X Bombois, P S C Heuberger: Errors-in-variables identification in dynamic networks. Proc. of the 19th IFAC World Congress, pp. 2335-2340, 2014. (Type: Inproceedings | Links)
B Günes, A G Dankers, P M J Van den Hof: Variance reduction for identification in dynamic networks. Proc. of the 19th IFAC World Congress, pp. 2842-2847, 2014. (Type: Inproceedings | Links)
A G Dankers, P M J Van den Hof, X Bombois: Direct and indirect continuous-time identification in dynamic networks. Proc. 53rd IEEE Conf. on Decision and Control (CDC), pp. 3334-3339, IEEE Los Angeles, CA, USA, 2014. (Type: Inproceedings | Links)

2013
A G Dankers, P M J Van den Hof, X Bombois, P S C Heuberger: Predictor input selection for two-stage identification in dynamic networks. Proc. 2013 European Control Conference (ECC), pp. 1422-1427, 2013. (Type: Inproceedings | Links)
A G Dankers, P M J Van den Hof, P S C Heuberger: Predictor input selection for direct identification in dynamic networks. Proc. 52nd IEEE Conf. on Decision and Control (CDC), pp. 4541–4546, IEEE 2013. (Type: Inproceedings | Links)

2012
A G Dankers, P M J Van den Hof, P S C Heuberger, X Bombois: Dynamic network structure identification with prediction error methods - basic examples. J Schoukens, R Bitmead (Ed.): Proc. 16th IFAC Symposium on System Identification, Brussels, Belgium, pp. 876-881, 2012. (Type: Inproceedings | Links)