Paul M. J. Van den Hof

ORCID

Publication Activity (10 Years)

Years Active: 1992-2023
Publications (10 Years): 82

Top Venues

CoRR

CDC

Autom.

IEEE Trans. Autom. Control.

Publications

Xiaodong Cheng, Shengling Shi, Ioannis Lestas, Paul M. J. Van den Hof
A Necessary Condition for Network Identifiability With Partial Excitation and Measurement. IEEE Trans. Autom. Control. 68 (11) (2023)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
On a canonical distributed controller in the behavioral framework. Syst. Control. Lett. 179 (2023)
Shengling Shi, Xiaodong Cheng, Paul M. J. Van den Hof
Single Module Identifiability in Linear Dynamic Networks With Partial Excitation and Measurement. IEEE Trans. Autom. Control. 68 (1) (2023)
Xavier Bombois, Kévin Colin, Paul M. J. Van den Hof, Håkan Hjalmarsson
On the informativity of direct identification experiments in dynamical networks. Autom. 148 (2023)
Stefanie J. M. Fonken, Karthik Raghavan Ramaswamy, Paul M. J. Van den Hof
Local Identification in Dynamic Networks using a Multi-Step Least Squares Method. CDC (2023)
E. M. M. Kivits, Paul M. J. Van den Hof
Identification of Diffusively Coupled Linear Networks Through Structured Polynomial Models. IEEE Trans. Autom. Control. 68 (6) (2023)
Shengling Shi, Xiaodong Cheng, Paul M. J. Van den Hof
Generic identifiability of subnetworks in a linear dynamic network: The full measurement case. Autom. 137 (2022)
E. M. M. Lizan Kivits, Paul M. J. Van den Hof
Local identification in diffusively coupled linear networks. CDC (2022)
Xiaodong Cheng, Shengling Shi, Paul M. J. Van den Hof
Allocation of Excitation Signals for Generic Identifiability of Linear Dynamic Networks. IEEE Trans. Autom. Control. 67 (2) (2022)
Stefanie J. M. Fonken, Karthik Raghavan Ramaswamy, Paul M. J. Van den Hof
A scalable multi-step least squares method for network identification with unknown disturbance topology. Autom. 141 (2022)
H. J. Dreef, Shengling Shi, Xiaodong Cheng, M. C. F. Donkers, Paul M. J. Van den Hof
Excitation Allocation for Generic Identifiability of Linear Dynamic Networks With Fixed Modules. IEEE Control. Syst. Lett. 6 (2022)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
On Data-Driven Control: Informativity of Noisy Input-Output Data With Cross-Covariance Bounds. IEEE Control. Syst. Lett. 6 (2022)
H. J. Dreef, Shengling Shi, Xiaodong Cheng, M. C. F. Donkers, Paul M. J. Van den Hof
Excitation allocation for generic identifiability of linear dynamic networks with fixed modules. CoRR (2022)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
Informativity conditions for data-driven control based on input-state data and polyhedral cross-covariance noise bounds. CoRR (2022)
Karthik Raghavan Ramaswamy, Giulio Bottegal, Paul M. J. Van den Hof
Learning linear modules in a dynamic network with missing node observations. CoRR (2022)
Karthik Raghavan Ramaswamy, Péter Zoltán Csurcsia, Johan Schoukens, Paul M. J. Van den Hof
A frequency domain approach for local module identification in dynamic networks. Autom. 142 (2022)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
On a Canonical Distributed Controller in the Behavioral Framework. CoRR (2022)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
On data-driven control: informativity of noisy input-output data with cross-covariance bounds. CoRR (2021)
Karthik Raghavan Ramaswamy, Péter Zoltán Csurcsia, Johan Schoukens, Paul M. J. Van den Hof
A frequency domain approach for local module identification in dynamic networks. CoRR (2021)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
H ∞ performance analysis and distributed controller synthesis for interconnected linear systems from noisy input-state data. CDC (2021)
Karthik Raghavan Ramaswamy, Giulio Bottegal, Paul M. J. Van den Hof
Learning linear modules in a dynamic network using regularized kernel-based methods. Autom. 129 (2021)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
Guaranteed $\mathcal{H}_\infty$ performance analysis and controller synthesis for interconnected linear systems from noisy input-state data. CoRR (2021)
E. M. M. Kivits, Paul M. J. Van den Hof
Identification of physical networks through structured polynomial models. CoRR (2021)
Stefanie J. M. Fonken, Karthik Raghavan Ramaswamy, Paul M. J. Van den Hof
A scalable multi-step least squares method for network identification with unknown disturbance topology. CoRR (2021)
Karthik Raghavan Ramaswamy, Paul M. J. Van den Hof
A Local Direct Method for Module Identification in Dynamic Networks With Correlated Noise. IEEE Trans. Autom. Control. 66 (11) (2021)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
Controller identification for data-driven model-reference distributed control. ECC (2021)
Venkatakrishnan C. Rajagopal, Karthik Raghavan Ramaswamy, Paul M. J. Van den Hof
Learning local modules in dynamic networks without prior topology information. CDC (2021)
Paul M. J. Van den Hof, Karthik Raghavan Ramaswamy
Learning local modules in dynamic networks. L4DC (2021)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
Data-driven distributed control: Virtual reference feedback tuning in dynamic networks. CDC (2020)
Venkatakrishnan C. Rajagopal, Karthik Raghavan Ramaswamy, Paul M. J. Van den Hof
A regularized kernel-based method for learning a module in a dynamic network with correlated noise. CDC (2020)
Shengling Shi, Xiaodong Cheng, Paul M. J. Van den Hof
Single module identifiability in linear dynamic networks with partial excitation and measurement. CoRR (2020)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
Data-driven distributed control: Virtual reference feedback tuning in dynamic networks. CoRR (2020)
Karthik Raghavan Ramaswamy, Giulio Bottegal, Paul M. J. Van den Hof
Learning linear modules in a dynamic network using regularized kernel-based methods. CoRR (2020)
Harm H. M. Weerts, Jonas Linder, Martin Enqvist, Paul M. J. Van den Hof
Abstractions of linear dynamic networks for input selection in local module identification. Autom. 117 (2020)
Rik J. C. van Esch, Shengling Shi, Antoine Bernas, Svitlana Zinger, Albert P. Aldenkamp, Paul M. J. Van den Hof
A Bayesian method for inference of effective connectivity in brain networks for detecting the Mozart effect. Comput. Biol. Medicine 127 (2020)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
Distributed $\mathscr{H}_2$ Control for Interconnected Discrete-Time Systems: A Dissipativity-based Approach. CoRR (2020)
Shengling Shi, Xiaodong Cheng, Paul M. J. Van den Hof
Generic identifiability of subnetworks in a linear dynamic network: the full measurement case. CoRR (2020)
Rik J. C. van Esch, Shengling Shi, Antoine Bernas, Svitlana Zinger, Albert P. Aldenkamp, Paul M. J. Van den Hof
A Bayesian method for inference of effective connectivity in brain networks for detecting the Mozart effect. CoRR (2020)
Paul M. J. Van den Hof, Karthik Raghavan Ramaswamy
Path-based data-informativity conditions for single module identification in dynamic networks. CDC (2020)
Karthik Raghavan Ramaswamy, Paul M. J. Van den Hof
A local direct method for module identification in dynamic networks with correlated noise. CoRR (2019)
Karthik Raghavan Ramaswamy, Paul M. J. Van den Hof, Arne G. Dankers
Generalized sensing and actuation schemes for local module identification in dynamic networks. CDC (2019)
Shengling Shi, Giulio Bottegal, Paul M. J. Van den Hof
Bayesian topology identification of linear dynamic networks. ECC (2019)
E. M. M. Lizan Kivits, Paul M. J. Van den Hof
A dynamic network approach to identification of physical systems. CDC (2019)
Paul M. J. Van den Hof, Karthik Raghavan Ramaswamy, Arne G. Dankers, Giulio Bottegal
Local module identification in dynamic networks with correlated noise: the full input case. CDC (2019)
Shengling Shi, Giulio Bottegal, Paul M. J. Van den Hof
Bayesian topology identification of linear dynamic networks. CoRR (2019)
Xiaodong Cheng, Shengling Shi, Paul M. J. Van den Hof
Allocation of Excitation Signals for Generic Identifiability of Dynamic Networks. CDC (2019)
Harm H. M. Weerts, Jonas Linder, Martin Enqvist, Paul M. J. Van den Hof
Abstractions of linear dynamic networks for input selection in local module identification. CoRR (2019)
Tuan T. Nguyen, Mircea Lazar, Hans Butler, Paul M. J. Van den Hof
An instrumental variable method for closed-loop identification of coreless linear motors. ACC (2018)
Tom Robert Vince Steentjes, Mircea Lazar, Paul M. J. Van den Hof
A recursive estimation approach to distributed identification of large-scale multi-input-single-output FIR systems. CoRR (2018)
Paul M. J. Van den Hof, Karthik Raghavan Ramaswamy, Arne G. Dankers, Giulio Bottegal
Local module identification in dynamic networks with correlated noise: the full input case. CoRR (2018)
Paul M. J. Van den Hof, Arne G. Dankers, Harm H. M. Weerts
Identification in dynamic networks. Comput. Chem. Eng. 109 (2018)
Muhammad Mohsin Siraj, Max G. Potters, Paul M. J. Van den Hof
Local module identification in dynamic networks: do more inputs guarantee smaller variance? CoRR (2018)
Harm H. M. Weerts, Paul M. J. Van den Hof, Arne G. Dankers
Identifiability of linear dynamic networks. Autom. 89 (2018)
Harm H. M. Weerts, Paul M. J. Van den Hof, Arne G. Dankers
Prediction error identification of linear dynamic networks with rank-reduced noise. Autom. 98 (2018)
Harm H. M. Weerts, Paul M. J. Van den Hof, Arne G. Dankers
Single Module Identifiability in Linear Dynamic Networks. CDC (2018)
Harm H. M. Weerts, Paul M. J. Van den Hof, Arne G. Dankers
Single module identifiability in linear dynamic networks. CoRR (2018)
Karthik Raghavan Ramaswamy, Giulio Bottegal, Paul M. J. Van den Hof
Local Module Identification in Dynamic Networks Using Regularized Kernel-Based Methods. CDC (2018)
Sofie Haesaert, Paul M. J. Van den Hof, Alessandro Abate
Data-driven and model-based verification via Bayesian identification and reachability analysis. Autom. 79 (2017)
Paul M. J. Van den Hof, Arne G. Dankers, Harm H. M. Weerts
Identification in Dynamic Networks. CoRR (2017)
Françoise Lamnabhi-Lagarrigue, Anuradha Annaswamy, Sebastian Engell, Alf J. Isaksson, Pramod P. Khargonekar, Richard M. Murray, Henk Nijmeijer, Tariq Samad, Dawn M. Tilbury, Paul M. J. Van den Hof
Systems & Control for the future of humanity, research agenda: Current and future roles, impact and grand challenges. Annu. Rev. Control. 43 (2017)
Harm H. M. Weerts, Paul M. J. Van den Hof, Arne G. Dankers
Prediction error identification of linear dynamic networks with rank-reduced noise. CoRR (2017)
Paul M. J. Van den Hof, Harm H. M. Weerts, Arne G. Dankers
Prediction error identification with rank-reduced output noise. ACC (2017)
Paul M. J. Van den Hof, Arne G. Dankers, Harm H. M. Weerts
From closed-loop identification to dynamic networks: Generalization of the direct method. CDC (2017)
Sofie Haesaert, Paul M. J. Van den Hof, Alessandro Abate
Experiment design for formal verification via stochastic optimal control. ECC (2016)
Leyla Özkan, Xavier Bombois, Jobert H. A. Ludlage, Cristian R. Rojas, Håkan Hjalmarsson, Per Erik Modén, Michael Lundh, Ton Backx, Paul M. J. Van den Hof
Advanced autonomous model-based operation of industrial process systems (Autoprofit): Technological developments and future perspectives. Annu. Rev. Control. 42 (2016)
Harm H. M. Weerts, Paul M. J. Van den Hof, Arne G. Dankers
Identifiability of dynamic networks with noisy and noise-free nodes. CoRR (2016)
Harm H. M. Weerts, Paul M. J. Van den Hof, Arne G. Dankers
Identification of dynamic networks operating in the presence of algebraic loops. CDC (2016)
Max G. Potters, Xavier Bombois, M. Mansoori, Paul M. J. Van den Hof
Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design. Int. J. Control 89 (8) (2016)
Arne G. Dankers, Paul M. J. Van den Hof, Xavier Bombois, Peter S. C. Heuberger
Identification of Dynamic Models in Complex Networks With Prediction Error Methods: Predictor Input Selection. IEEE Trans. Autom. Control. 61 (4) (2016)
Max G. Potters, Xavier Bombois, Paul M. J. Van den Hof
Experiment time minimisation under parameter accuracy constraints and time-domain signal amplitude bounds. ECC (2016)
Sofie Haesaert, Alessandro Abate, Paul M. J. Van den Hof
Verification of General Markov Decision Processes by Approximate Similarity Relations and Policy Refinement. QEST (2016)
Muhammad Mohsin Siraj, Paul M. J. Van den Hof, Jan Dirk Jansen
Risk management in oil reservoir water-flooding under economic uncertainty. CDC (2015)
Arne G. Dankers, Paul M. J. Van den Hof
Non-parametric identification in dynamic networks. CDC (2015)
Marco Forgione, Xavier Bombois, Paul M. J. Van den Hof
Data-driven model improvement for model-based control. Autom. 52 (2015)
Sofie Haesaert, Paul M. J. Van den Hof, Alessandro Abate
Data-driven property verification of grey-box systems by Bayesian experiment design. ACC (2015)
Arne G. Dankers, Paul M. J. Van den Hof, Xavier Bombois, Peter S. C. Heuberger
Errors-in-variables identification in dynamic networks - Consistency results for an instrumental variable approach. Autom. 62 (2015)
Sofie Haesaert, Paul M. J. Van den Hof, Alessandro Abate
Observer-based correct-by-design controller synthesis. CoRR (2015)
Sofie Haesaert, Alessandro Abate, Paul M. J. Van den Hof
Correct-by-design output feedback of LTI systems. CDC (2015)
Sofie Haesaert, Alessandro Abate, Paul M. J. Van den Hof
Data-driven and model-based verification: A Bayesian identification approach. CDC (2015)
Sofie Haesaert, Paul M. J. Van den Hof, Alessandro Abate
Data-driven and Model-based Verification: a Bayesian Identification Approach. CoRR (2015)
Max G. Potters, Marco Forgione, Xavier Bombois, Paul M. J. Van den Hof
Least-costly experiment design for uni-parametric linear models: An analytical approach. ECC (2015)
Ali Mesbah, Xavier Bombois, Marco Forgione, Håkan Hjalmarsson, Paul M. J. Van den Hof
Least costly closed-loop performance diagnosis and plant re-identification. Int. J. Control 88 (11) (2015)
Marco Forgione, Xavier Bombois, Paul M. J. Van den Hof, Håkan Hjalmarsson
Experiment design for parameter estimation in nonlinear systems based on multilevel excitation. ECC (2014)
Arne G. Dankers, Paul M. J. Van den Hof, Xavier Bombois
Direct and indirect continuous-time identification in dynamic networks. CDC (2014)
Paul M. J. Van den Hof, Arne G. Dankers, Peter S. C. Heuberger, Xavier Bombois
Identification of dynamic models in complex networks with prediction error methods - Basic methods for consistent module estimates. Autom. 49 (10) (2013)
Marco Forgione, Xavier Bombois, Paul M. J. Van den Hof
Experiment design for batch-to-batch model-based learning control. ACC (2013)
Skander Taamallah, Xavier Bombois, Paul M. J. Van den Hof
Affine LPV modeling: An H∞ based approach. CDC (2013)
Arne G. Dankers, Paul M. J. Van den Hof, Peter S. C. Heuberger
Predictor input selection for direct identification in dynamic networks. CDC (2013)
Arne G. Dankers, Paul M. J. Van den Hof, Xavier Bombois, Peter S. C. Heuberger
Predictor input selection for two stage identification in dynamic networks. ECC (2013)
Marco Forgione, Ali Mesbah, Xavier Bombois, Paul M. J. Van den Hof
Iterative Learning Control of supersaturation in batch cooling crystallization. ACC (2012)
Skander Taamallah, Xavier Bombois, Paul M. J. Van den Hof
Optimal control for power-off landing of a small-scale helicopter a pseudospectral approach. ACC (2012)
Ali Mesbah, Zoltan K. Nagy, Adrie E. M. Huesman, Herman J. M. Kramer, Paul M. J. Van den Hof
Nonlinear Model-Based Control of a Semi-Industrial Batch Crystallizer Using a Population Balance Modeling Framework. IEEE Trans. Control. Syst. Technol. 20 (5) (2012)
Ali Mesbah, Xavier Bombois, Marco Forgione, Jobert H. A. Ludlage, Per Erik Modén, Håkan Hjalmarsson, Paul M. J. Van den Hof
A unified experiment design framework for detection and identification in closed-loop performance diagnosis. CDC (2012)
Arne G. Dankers, Paul M. J. Van den Hof, Peter S. C. Heuberger, Xavier Bombois
Dynamic network identification using the direct prediction-error method. CDC (2012)
Roland Tóth, Marco Lovera, Peter S. C. Heuberger, Matteo Corno, Paul M. J. Van den Hof
On the Discretization of Linear Fractional Representations of LPV Systems. IEEE Trans. Control. Syst. Technol. 20 (6) (2012)
Marco Forgione, Ali Mesbah, Xavier Bombois, Paul M. J. Van den Hof
Batch-to-batch strategies for cooling crystallization. CDC (2012)
Paul M. J. Van den Hof, Arne G. Dankers, Peter S. C. Heuberger, Xavier Bombois
Identification in dynamic networks with known interconnection topology. CDC (2012)
Ali Mesbah, Xavier Bombois, Jobert H. A. Ludlage, Paul M. J. Van den Hof
Closed-loop performance diagnosis using prediction error identification. CDC/ECC (2011)
Roland Tóth, Marc van de Wal, Peter S. C. Heuberger, Paul M. J. Van den Hof
LPV identification of high performance positioning devices. ACC (2011)
Roland Tóth, Jan C. Willems, Peter S. C. Heuberger, Paul M. J. Van den Hof
The Behavioral Approach to Linear Parameter-Varying Systems. IEEE Trans. Autom. Control. 56 (11) (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Paul M. J. Van den Hof