Paul M. J. Van den Hof

发表

Nonlinear Model-Based Control of a Semi-Industrial Batch Crystallizer Using a Population Balance Modeling Framework

Zoltan K. Nagy, Ali Mesbah, Adrie E. M. Huesman, 2012, IEEE Transactions on Control Systems Technology.

Call for papers for an Automatica Special Issue on Data-based modelling and system identification

Paul M. J. Van den Hof, 2003, Autom..

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

Mircea Lazar, Paul M. J. Van den Hof, Tom R. V. Steentjes, 2018, ArXiv.

Allocation of Excitation Signals for Generic Identifiability of Dynamic Networks

Xiaodong Cheng, Paul M. J. Van den Hof, Shengling Shi, 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

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

Svitlana Zinger, Paul M. J. Van den Hof, Shengling Shi, 2020, Comput. Biol. Medicine.

An instrumental variable method for closed-loop identification of coreless linear motors

Mircea Lazar, Hans Butler, Paul M. J. Van den Hof, 2018, 2018 Annual American Control Conference (ACC).

Multivariable feedback relevant system identification of a wafer stepper system

Raymond A. de Callafon, Paul M. J. Van den Hof, P. V. D. Hof, 2001, IEEE Trans. Control. Syst. Technol..

Extended Ho-Kalman algorithm for systems represented in generalized orthonormal bases

Zoltán Szabó, Jozsef Bokor, Peter S. C. Heuberger, 2000, Autom..

Closed-loop performance diagnosis using prediction error identification

Xavier Bombois, Ali Mesbah, Paul M. J. Van den Hof, 2011, IEEE Conference on Decision and Control and European Control Conference.

Integrated dynamic optimization and control in reservoir engineering using locally identified linear models

Gijs van Essen, Jan Dirk Jansen, Paul M. J. Van den Hof, 2010, 49th IEEE Conference on Decision and Control (CDC).

LPV system identification with globally fixed orthonormal basis functions

Roland Tóth, Peter S. C. Heuberger, Paul M. J. Van den Hof, 2007, 2007 46th IEEE Conference on Decision and Control.

Test for local structural identifiability of high-order non-linearly parametrized state space models

Paul M. J. Van den Hof, Hans G. M. Dötsch, P. V. D. Hof, 1996, Autom..

Single Module Identifiability in Linear Dynamic Networks

Arne G. Dankers, Paul M. J. Van den Hof, Harm H. M. Weerts, 2018, 2018 IEEE Conference on Decision and Control (CDC).

Asymptotically optimal orthonormal basis functions for LPV system identification

Roland Tóth, Peter S. C. Heuberger, Paul M. J. Van den Hof, 2009, Autom..

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

Paul M. J. Van den Hof, Venkatakrishnan C. Rajagopal, Karthik R. Ramaswamy, 2020, 2020 59th IEEE Conference on Decision and Control (CDC).

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

Giulio Bottegal, Arne G. Dankers, Paul M. J. Van den Hof, 2018, 2019 IEEE 58th Conference on Decision and Control (CDC).

Observer-based correct-by-design controller synthesis pdf

Sofie Haesaert, Alessandro Abate, Paul M. J. Van den Hof, 2015, ArXiv.

Systems & Control for the future of humanity, research agenda: Current and future roles, impact and grand challenges

Anuradha M. Annaswamy, Henk Nijmeijer, Richard M. Murray, 2017, Annu. Rev. Control..

Identification and control - Closed-loop issues

Paul M. J. Van den Hof, Ruud J. P. Schrama, P. V. D. Hof, 1995, Autom..

On the Discretization of Linear Fractional Representations of LPV Systems

Marco Lovera, Roland Tóth, Peter S. C. Heuberger, 2009, IEEE Transactions on Control Systems Technology.

Virtual closed loop identification: A generalized tool for identification in closed loop

Graham C. Goodwin, Juan C. Agüero, Paul M. J. Van den Hof, 2008, 2008 47th IEEE Conference on Decision and Control.

Closed-loop identification of multivariable processes with part of the inputs controlled

Martijn Leskens, Paul M. J. Van den Hof, P. V. D. Hof, 2007, Proceedings of the 2004 American Control Conference.

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

Xiaodong Cheng, Paul M. J. Van den Hof, Shengling Shi, 2020, ArXiv.

Quantification of uncertainty in transfer function estimation: a mixed probabilistic-worst-case approach

Paul M. J. Van den Hof, Douwe K. de Vries, P. V. D. Hof, 1995, Autom..

On the Discretization of Linear Fractional Representations of LPV Systems

Marco Lovera, Matteo Corno, Roland Tóth, 2012, IEEE Trans. Control. Syst. Technol..

Data-driven property verification of grey-box systems by bayesian experiment design

Sofie Haesaert, Alessandro Abate, Paul M. J. Van den Hof, 2015, 2015 American Control Conference (ACC).

Local module identification in dynamic networks: do more inputs guarantee smaller variance? pdf

Max G. Potters, Paul M. J. Van den Hof, M. Mohsin Siraj, 2018, ArXiv.

Order and structural dependence selection of LPV-ARX models using a nonnegative garrote approach

Roland Tóth, Peter S. C. Heuberger, Christian Lyzell, 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

Identification of Dynamic Models in Complex Networks With Prediction Error Methods: Predictor Input Selection

Xavier Bombois, Arne G. Dankers, Peter S. C. Heuberger, 2016, IEEE Transactions on Automatic Control.

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

Paul M. J. Van den Hof, Karthik R. Ramaswamy, K. R. Ramaswamy, 2020, 2020 59th IEEE Conference on Decision and Control (CDC).

Control-relevant Identification and Servo Design for a Compact Disc Player

Raymond A. de Callafon, Paul M. J. Van den Hof, P. V. D. Hof, 2002 .

Pieter Eykhoff, 1929-2000

Pedro Albertos, Paul M. J. Van den Hof, 2001, Autom..

Experiment design for formal verification via stochastic optimal control

Sofie Haesaert, Alessandro Abate, Paul M. J. Van den Hof, 2016, 2016 European Control Conference (ECC).

Flexible model structures for LPV identification with static scheduling dependency

Roland Tóth, Peter S. C. Heuberger, Paul M. J. Van den Hof, 2008, 2008 47th IEEE Conference on Decision and Control.

Introduction to the special issue on data-based modelling and system identification

Bo Wahlberg, Torsten Söderström, Siep Weiland, 2005, Autom..

Experiment design for parameter estimation in nonlinear systems based on multilevel excitation

Marco Forgione, Håkan Hjalmarsson, Xavier Bombois, 2014, 2014 European Control Conference (ECC).

Experiment time minimisation under parameter accuracy constraints and time-domain signal amplitude bounds

Xavier Bombois, Max G. Potters, Paul M. J. Van den Hof, 2016, 2016 European Control Conference (ECC).

Identification in dynamic networks with known interconnection topology

Xavier Bombois, Arne G. Dankers, Peter S. C. Heuberger, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

Model sets and parametrizations for identification of multivariable equation error models

Paul M. J. Van den Hof, 1994, Autom..

Validity of the standard cross-correlation test for model structure validation

Xavier Bombois, Sippe G. Douma, Paul M. J. Van den Hof, 2008, Autom..

The Behavioral Approach to Linear Parameter-Varying Systems

Jan C. Willems, Roland Tóth, Peter S. C. Heuberger, 2011, IEEE Transactions on Automatic Control.

Load dynamics in piezoelectric actuation

Georg Schitter, Paul M. J. Van den Hof, J. van Eijk, 2009, 2009 European Control Conference (ECC).

Delay structure conditions for identifiability of closed loop systems

Paul M. J. Van den Hof, Douwe K. de Vries, Peter Schoen, 1992, Autom..

Dynamic network identification using the direct prediction-error method

Xavier Bombois, Arne G. Dankers, Peter S. C. Heuberger, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

Non-parametric identification in dynamic networks

Arne G. Dankers, Paul M. J. Van den Hof, 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

Informative data and identifiability in LPV-ARX prediction-error identification

Xavier Bombois, Roland Tóth, Arne G. Dankers, 2011, IEEE Conference on Decision and Control and European Control Conference.

Control of cavity flow based on a macroscopic observation

Dimitri Jeltsema, Paul M. J. Van den Hof, S. Djordjevic, 2009, 2009 European Control Conference (ECC).

Identifiability of linear dynamic networks

Arne G. Dankers, Paul M. J. Van den Hof, Harm H. M. Weerts, 2016, Autom..

On Discriminable Model Sets in Residual-Based System Identification

Paul M. J. Van den Hof, 1990 .

Risk management in oil reservoir water-flooding under economic uncertainty

Jan Dirk Jansen, Paul M. J. Van den Hof, M. Mohsin Siraj, 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

Orthonormal Basis Functions in Time and Frequency Domain: Hambo Transform Theory

Bo Wahlberg, Peter S. C. Heuberger, Paul M. J. Van den Hof, 2003, SIAM J. Control. Optim..

Consistent parameter bounding identification for linearly parametrized model sets

Paul M. J. Van den Hof, Richard G. Hakvoort, P. V. D. Hof, 1995, Autom..

Identification of Normalised Coprime Plant Factors from Closed-loop Experimental Data

Raymond A. de Callafon, Okko H. Bosgra, Paul M. J. Van den Hof, 1995, Eur. J. Control.

An indirect method for transfer function estimation from closed loop data

Paul M. J. Van den Hof, Ruud J. P. Schrama, P. V. D. Hof, 1993, Autom..

A unified experiment design framework for detection and identification in closed-loop performance diagnosis

Marco Forgione, Håkan Hjalmarsson, Xavier Bombois, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

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

Xiaodong Cheng, Paul M. J. Van den Hof, Shengling Shi, 2020, ArXiv.

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

Arne G. Dankers, Paul M. J. Van den Hof, Harm H. M. Weerts, 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

A virtual closed loop method for closed loop identification

Graham C. Goodwin, Juan C. Agüero, Paul M. J. Van den Hof, 2011, Autom..

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

Giulio Bottegal, Paul M. J. Van den Hof, Karthik R. Ramaswamy, 2018, 2018 IEEE Conference on Decision and Control (CDC).

Correct-by-design output feedback of LTI systems

Sofie Haesaert, Alessandro Abate, Paul M. J. Van den Hof, 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

Relations between uncertainty structures in identification for robust control

Sippe G. Douma, Paul M. J. Van den Hof, S. G. Douma, 2005, Autom..

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

Jonas Linder, Paul M. J. Van den Hof, Martin Enqvist, 2019, Autom..

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

Arne G. Dankers, Paul M. J. Van den Hof, Harm H. M. Weerts, 2017, Autom..

System identification with generalized orthonormal basis functions

Jozsef Bokor, Peter S. C. Heuberger, Paul M. J. Van den Hof, 1995, Autom..

Data-driven and model-based verification: A Bayesian identification approach

Sofie Haesaert, Alessandro Abate, Paul M. J. Van den Hof, 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

A Unified Transform for LTI Systems—Presented as a (Generalized) Frame

Arie Feuer, Peter S. C. Heuberger, Paul M. J. Van den Hof, 2006, EURASIP J. Adv. Signal Process..

On the relation between a bias-eliminated least-squares (BELS) and an IV estimator in closed-loop identification

Marion Gilson, Paul M. J. Van den Hof, 2001, Autom..

Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design

Xavier Bombois, Max G. Potters, Paul M. J. Van den Hof, 2016, Int. J. Control.

Analysis of closed-loop identification with a tailor-made parametrization

Paul M. J. Van den Hof, Edwin T. van Donkelaar, 1997, 1997 European Control Conference (ECC).

Errors-in-variables identification in dynamic networks - Consistency results for an instrumental variable approach

Xavier Bombois, Arne G. Dankers, Peter S. C. Heuberger, 2015, Autom..

Experiment design for batch-to-batch model-based learning control

Marco Forgione, Xavier Bombois, Paul M. J. Van den Hof, 2013, 2013 American Control Conference.

Affine LPV modeling: An H∞ based approach

Xavier Bombois, Skander Taamallah, Paul M. J. Van den Hof, 2013, 52nd IEEE Conference on Decision and Control.

Scalable distributed and decentralized $\mathscr{H}_2$ controller synthesis for interconnected linear discrete-time systems

Paul M. J. Van den Hof, Tom R. V. Steentjes, Mircea Lazar, 2020 .

Distributed $\mathscr{H}_2$ Control for Interconnected Discrete-Time Systems: A Dissipativity-based Approach pdf

Mircea Lazar, Paul M. J. Van den Hof, Tom R. V. Steentjes, 2020, ArXiv.

Controller tuning freedom under plant identification uncertainty: double Youla beats gap in robust stability

Sippe G. Douma, Okko H. Bosgra, Paul M. J. Van den Hof, 2003, Autom..

Direct and indirect continuous-time identification in dynamic networks

Xavier Bombois, Arne G. Dankers, Paul M. J. Van den Hof, 2014, 53rd IEEE Conference on Decision and Control.

Bayesian topology identification of linear dynamic networks

Giulio Bottegal, Paul M. J. Van den Hof, Shengling Shi, 2019, 2019 18th European Control Conference (ECC).

Identification in dynamic networks

Arne G. Dankers, Paul M. J. Van den Hof, Harm H. M. Weerts, 2017, Comput. Chem. Eng..

Batch-to-batch strategies for cooling crystallization

Marco Forgione, Xavier Bombois, Ali Mesbah, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

Asymptotic variance expressions for closed-loop identification

Michel Gevers, Lennart Ljung, Paul M. J. Van den Hof, 2001, Autom..

A behavioral approach to LPV systems

Jan C. Willems, Roland Tóth, Peter S. C. Heuberger, 2009, 2009 European Control Conference (ECC).

Predictor input selection for two stage identification in dynamic networks

Xavier Bombois, Arne G. Dankers, Peter S. C. Heuberger, 2013, 2013 European Control Conference (ECC).

Model Set Determination and its Application to the Control of Compact Disc Players

Paul M. J. Van den Hof, Hans G. M. Dötsch, T. Zhou, 1998, Eur. J. Control.

Least costly identification experiment for control

Xavier Bombois, Gérard Scorletti, Michel Gevers, 2006, Autom..

Towards automatic control of scanning transmission electron microscopes

Arturo Tejada, Arnold Jan den Dekker, Paul M. J. Van den Hof, 2009, 2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC).

Identification of dynamic networks operating in the presence of algebraic loops

Arne G. Dankers, Paul M. J. Van den Hof, Harm H. M. Weerts, 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

Final comments by the Authors

Paul M. J. Van den Hof, Edwin T. van Donkelaar, 2000, Eur. J. Control.

Minimal partial realization from generalized orthonormal basis function expansions

Zoltán Szabó, Jozsef Bokor, Peter S. C. Heuberger, 2002, Autom..

Instrumental variable methods for closed-loop system identification

Marion Gilson, Paul M. J. Van den Hof, P. V. D. Hof, 2005, Autom..

Identifiability of dynamic networks with noisy and noise-free nodes pdf

Arne G. Dankers, Paul M. J. Van den Hof, Harm H. M. Weerts, 2016, ArXiv.

A dynamic network approach to identification of physical systems

Paul M. J. Van den Hof, E. M. M. Lizan Kivits, P. V. D. Hof, 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

Predictor input selection for direct identification in dynamic networks

Arne G. Dankers, Peter S. C. Heuberger, Paul M. J. Van den Hof, 2013, 52nd IEEE Conference on Decision and Control.

Allocation of Excitation Signals for Generic Identifiability of Linear Dynamic Networks

Xiaodong Cheng, Paul M. J. Van den Hof, Shengling Shi, 2019, IEEE Transactions on Automatic Control.

Data-driven and model-based verification via Bayesian identification and reachability analysis

Sofie Haesaert, Alessandro Abate, Paul M. J. Van den Hof, 2017, Autom..

Identification of dynamic models in complex networks with prediction error methods - Basic methods for consistent module estimates

Xavier Bombois, Arne G. Dankers, Peter S. C. Heuberger, 2013, Autom..

Effect of model structure and signal-to-noise ratio on finite-time uncertainty bounding in prediction error identification

Xavier Bombois, Arnold Jan den Dekker, Märta Barenthin Syberg, 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

Lexicographic optimization of multiple economic objectives in oil production from petroleum reservoirs

Gijs van Essen, Jan Dirk Jansen, Paul M. J. Van den Hof, 2010, Proceedings of the 2010 American Control Conference.

Data-driven model improvement for model-based control

Marco Forgione, Xavier Bombois, Paul M. J. Van den Hof, 2015, Autom..

Iterative Learning Control of supersaturation in batch cooling crystallization

Marco Forgione, Xavier Bombois, Ali Mesbah, 2012, 2012 American Control Conference (ACC).

Approximate identification with closed-loop performance criterion and application to LQG feedback design

Paul M. J. Van den Hof, Ruud J. P. Schrama, Richard G. Hakvoort, 1994, Autom..

Multivariable frequency domain identification using IV-based linear regression

Paul M. J. Van den Hof, Rogier S. Blom, 2010, 49th IEEE Conference on Decision and Control (CDC).

Advanced autonomous model-based operation of industrial process systems (Autoprofit): Technological developments and future perspectives

Håkan Hjalmarsson, Xavier Bombois, Cristian R. Rojas, 2016, Annu. Rev. Control..

Optimal control for power-off landing of a small-scale helicopter a pseudospectral approach

Xavier Bombois, Skander Taamallah, Paul M. J. Van den Hof, 2012, 2012 American Control Conference (ACC).

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

Arne G. Dankers, Paul M. J. Van den Hof, Karthik R. Ramaswamy, 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

Prediction error identification with rank-reduced output noise

Arne G. Dankers, Paul M. J. Van den Hof, Harm H. M. Weerts, 2017, 2017 American Control Conference (ACC).

Orthonormal basis selection for LPV system identification, the Fuzzy-Kolmogorov c-Max approach

Roland Tóth, Peter S. C. Heuberger, Paul M. J. Van den Hof, 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

Least costly closed-loop performance diagnosis and plant re-identification

Marco Forgione, Håkan Hjalmarsson, Xavier Bombois, 2015, Int. J. Control.

Identification of diffusively coupled linear networks through structured polynomial models

Paul M. J. Van den Hof, E. M. M. Kivits, 2021 .

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

Xiaodong Cheng, Paul M. J. Van den Hof, Shengling Shi, 2022, Automatica.

Single Module Identifiability in Linear Dynamic Networks With Partial Excitation and Measurement pdf

Xiaodong Cheng, Paul M. J. Van den Hof, Shengling Shi, 2020, IEEE Transactions on Automatic Control.

Controller identification for data-driven model-reference distributed control

Mircea Lazar, Paul M. J. Van den Hof, Tom Robert Vince Steentjes, 2021, 2021 European Control Conference (ECC).

Learning local modules in dynamic networks

Paul M. J. Van den Hof, Karthik R. Ramaswamy, 2021, L4DC.

Identifiability in Dynamic Acyclic Networks with Partial Excitations and Measurements

Ioannis Lestas, Paul M. J. Van den Hof, Shengling Shi, 2022 .

Controller tuning freedom under plant identification uncertainty: double Youla beats gap in robust stability

Sippe G. Douma, Okko H. Bosgra, Paul M. J. Van den Hof, 2003, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

Identi cation of Probabilistic System Uncertainty Regions byExplicit Evaluation of Bias and Variance Errors zRichard

Paul M. J. Van den Hof, P. V. D. Hof, G., 1997 .

S Y ] 1 4 M ar 2 01 9 Bayesian topology identification of linear dynamic networks

Giulio Bottegal, Paul M. J. Van den Hof, Shengling Shi, 2019 .

IDENTIFICATION FOR CONTROL

Raymond A. de Callafon, Paul M. J. Van den Hof, P. V. D. Hof, 2009 .

INTEGRATING MPC AND RTO IN THE PROCESS INDUSTRY BY ECONOMIC DYNAMIC LEXICOGRAPHIC OPTIMIZATION ; AN OPEN-LOOP EXPLORATION

Okko H. Bosgra, Adrie E. M. Huesman, Paul M. J. Van den Hof, 2008 .

Model predictive control with generalized input parametrization

Okko H. Bosgra, Paul M. J. Van den Hof, Edwin T. van Donkelaar, 1999, 1999 European Control Conference (ECC).

Control Relevant Identi cation for H 1-norm based Performance Speci cations

Raymond A. de Callafon, Paul M. J. Van den Hof, 1995 .