P. V. D. Hof

发表

Multivariable closed-loop identification: from indirect identification to dual-Youla parametrization

P. V. D. Hof, R. D. Callafon, 1996 .

Modelling and Identification with Rational Orthogonal Basis Functions

B. Wahlberg, B. Ninness, P. V. D. Hof, 2000 .

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

Giulio Bottegal, Paul M.J. Van den Hof, Karthik R. Ramaswamy, 2020, Autom..

Relation between uncertainty structures in identification for robust control

S. G. Douma, P. V. D. Hof, 2003 .

Identification of probabilistic system uncertainty regions by explicit evaluation of bias and variance errors

P. V. D. Hof, R. Hakvoort, 1997, IEEE Trans. Autom. Control..

Suboptimal feedback control by a scheme of iterative identification and control design

P. V. D. Hof, R. D. Callafon, 1997 .

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..

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.

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).

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..

A behavioral approach to LPV systems

Jan C. Willems, Roland Tóth, Peter S. C. Heuberger, 2009, 2009 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).

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 generalized orthonormal basis for linear dynamical systems

P. V. D. Hof, O. Bosgra, P. Heuberger, 1995, IEEE Trans. Autom. Control..

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..

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

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

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).

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.

Crucial Aspects of Zero-Order Hold LPV State-Space System Discretization ⋆

P. V. D. Hof, P. Heuberger, R. Tóth, 2008 .

Instrumental variable methods for closed-loop system identification

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

A unified approach to stability robustness for uncertainty descriptions based on fractional model representations

P. V. D. Hof, R. D. Callafon, P. Bongers, 1996, IEEE Trans. Autom. Control..

Modeling and Identification of Linear Parameter-Varying Systems, an Orthonormal Basis Function Approach

P.M.J. Van den Hof, Peter S. C. Heuberger, R. T. Tóth, 2004 .

IV methods for closed-loop system identification

P. V. D. Hof, M. Gilson, 2003 .

A REFINED IV METHOD FOR CLOSED-LOOP SYSTEM IDENTIFICATION

P. Young, P. V. D. Hof, M. Gilson, 2006 .

Asymptotic Variance Expressions for Closed-Loop Identification and Their Relevance in Identification for Control

L. Ljung, M. Gevers, P. V. D. Hof, 1997 .

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

P. V. D. Hof, E. V. Donkelaar, 1997 .

Identi cation of normalized coprime plant factors from closed loop experimental data z

Ruud J. P. Schrama, P. V. D. Hof, R. D. Callafon, 1995 .

Optimal instrumental variable method for closed-loop identification

P. Young, P. V. D. Hof, M. Gilson, 2011 .

Finite Sample Confidence Regions for Parameters in Prediction Error Identification using Output Error Models

P. V. D. Hof, X. Bombois, A. J. D. Dekker, 2008 .

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..

Modeling : An H ∞ Based Approach

P. V. D. Hof, X. Bombois, S. Taamallah, 2013 .

System order and structure indices of linear systems in polynomial form

P. V. D. Hof, 1992 .

Approximate identification with linear regression models

P. V. D. Hof, 1991 .

On the Order and Structural Indices of Linear Systems Represented in Polynomial Form

P. V. D. Hof, 1990 .

Bang-Bang Control in Reservoir Flooding

P. V. D. Hof, O. Bosgra, J. Jansen, 2006 .

Process Control-Relevant and Closed-Loop Identification

Raymond A. de Callafon, Paul M.J. Van den Hof, P. V. D. Hof, 1999 .

IN IDENTIFICATION , MODELLING AND CONTROL Progress Report on Research Activities in the Mechanical Engineering Systems and Control Group

P. V. D. Hof, G. H. Bosgra, 2011 .

Quantification of model uncertainty from data: input design, interpolation, and connection with robust control design specifications

P. V. D. Hof, D. D. Vries, 1992 .

Equation error versus output error methods

P. V. D. Hof, Y. Tomita, A. Damen, 1992 .

Some asymptotic properties of multivariable models identified by equation error techniques

P. V. D. Hof, P.H.M. Janssen, 1986 .

A control oriented study on the numerical solution of the population balance equation for crystallization processes

P. V. D. Hof, H. Kramer, A. Mesbah, 2009 .

Identification of model error bounds in l1- and H∞-norm

Paul M.J. Van den Hof, Richard G. Hakvoort, P. V. D. Hof, 1994 .

Frequency domain identification with generalized orthonormal basis functions

P. V. D. Hof, D. D. Vries, P.M.J. Van den Hof, 1995, IEEE Trans. Autom. Control..

IDENTIFICATION FOR CONTROL

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

Frequency domain identification with generalized orthonormal basis functions

P. V. D. Hof, D. D. Vries, P.M.J. Van den Hof, 1998, IEEE Trans. Autom. Control..

Determining Identifiable Parameterizations for Large-scale Physical Models in Reservoir Engineering

Paul M.J. Van den Hof, Jan Dirk Jansen, Okko H. Bosgra, 2008 .

An iterative algorithm for learning dynamic networks with correlated noise

K. R. Ramaswamy, P. V. D. Hof, V. C. Rajagopal, 2019 .

Closed‐loop identification of a continuous crystallization process

P. V. D. Hof, R. Eek, J. Both, 1996 .

Sensor configuration problem : application to a membrane separation unit

Leyla Özkan, Paul M.J. Van den Hof, Siep Weiland, 2016 .

AsymptoticallyOptimalOrthonormalBasis Functions for LPVSystem Identification ?

P. V. D. Hof, P. Heuberger, R. Tóth, 2009 .

LPV Modelling with A ffi ne Dependence : A Local H ∞ Approach

P. V. D. Hof, X. Bombois, R. Tóth, 2016 .

Experiment design for parameter estimation of a dynamical system in a nonlinear model structure based on multilevel excitation

H. Hjalmarsson, P. V. D. Hof, X. Bombois, 2013 .

A Uni ed Approach to Stability Robustness for Uncertainty Descriptions based on Fractional Model Representations

P. V. D. Hof, RepresentationsR, .. A. de, 1994 .

Control relevant identi � cation for H �

P. V. D. Hof, R. D. Callafon, 2009 .

eview n outlook on robust model predictive control algorithms : Reflections n performance and computational aspects

M. B. Saltik, P. V. D. Hof, S. Weiland, 2017 .

A Unifled Approach to Stability Robustness for Uncertainty Descriptions based on Fbactional Model Representations

P. V. D. Hof, Raymond A. de Callafontr, P. Lu, 2022 .

IdentificationofDynamicModelsinComplexNetworkswith PredictionErrorMethods-BasicMethodsforConsistentModule Estimates

P. V. D. Hof, P. Heuberger, X. Bombois, 2012 .

Least costly identificationexperiment for control

M. Gevers, P. V. D. Hof, R. Hildebrand, 2006 .

Single module identification in dynamic networks-the current status ?

K. R. Ramaswamy, P. V. D. Hof, 2020 .

Wavelets and variance reduction in non-parametric transfer function estimation

S. G. Douma, P. V. D. Hof, T. Hoog, 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

A mixed deterministic-probabilistic approach for quantifying uncertainty in Transfer Function Estimation

P. V. D. Hof, D. D. Vries, 1994 .

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

K. R. Ramaswamy, P. V. D. Hof, S. Fonken, 2021, Autom..

Prediction error identification in physical networks

P. V. D. Hof, E. Kivits, 2019 .

Partial Realization in Generalized Bases: Algorithm and Example

P. V. D. Hof, P. Heuberger, T. Hoog, 2000 .

Realization algorithms for expansions in generalized orthonormal basis functions

P. V. D. Hof, P. Heuberger, J. Bokor, 1999 .

Frequency Domain Identi cation withGeneralized Orthonormal Basis

P. V. D. Hof, FunctionszDouwe, K. De, 1995 .

Validation Test Based Parameter Uncertainty Versus Analysis-Based Confidence Bounds

S. G. Douma, P. V. D. Hof, X. Bombois, 2003 .

New insights in closed-loop identification with bias-eliminated least-squares (BELS)

P. V. D. Hof, M. Gilson, 2001, 2001 European Control Conference (ECC).

IDENTIFICATION, MODELLING AND CONTROL SELECTED TOPICS IN IDENTIFICATION, MODELLING AND CONTROL

P. V. D. Hof, H. Bosgra, 2011 .

Data-drivenmodelimprovementformodel-basedcontrol

P. V. D. Hof, X. Bombois, Marco Forgione, 2013 .

On a simplified modelling approach to SMB process for use in optimization

Bo Wahlberg, Michel Kinnaert, P.M.J. Van den Hof, 2003 .

An outlook on robust model predictive control algorithms: Reflections on performance and computational aspects

Leyla Özkan, Jobert Ludlage, Siep Weiland, 2018 .

Learning linear modules in a dynamic network with missing node observations

K. R. Ramaswamy, P. V. D. Hof, Giulio Bottegal, 2022, ArXiv.

Identification of Diffusively Coupled Linear Networks Through Structured Polynomial Models

P. V. D. Hof, E. Kivits, 2021, IEEE Transactions on Automatic Control.

Active Deformation Control for a Magnetically Levitated Planar Motor Mover

P. V. D. Hof, R. Tóth, H. Butler, 2022, IEEE transactions on industry applications.

Identifiability of linear dynamic networks through switching modules

H. J. Dreef, P. V. D. Hof, M. Donkers, 2021, IFAC-PapersOnLine.

Affine LPV Modeling: An H-infinity Based Approach

P.M.J. Van den Hof, Skander Taamallah, Xja Bombois, 2014 .

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.

Identification of a Pilot Plant Crystallization Process with Output Error Methods

P.M.J. Van den Hof, S. De Wolf, P. V. D. Hof, 1992 .

Boundary control of two-phase fluid flow using the Laplace-space domain

Okko H. Bosgra, Paul M. J. Van den Hof, P. V. D. Hof, 2011, Proceedings of the 2011 American Control Conference.

Boundary actuation structure of linearized two-phase flow

P M J Van den Hof, P. V. D. Hof, O. Bosgra, 2010, Proceedings of the 2010 American Control Conference.

Naive Approximate Realizations of Noisy Data

P. V. D. Hof, A. Damen, A. Hajdasiński, 1984 .

Multivariable partial realization and the aspect of uniqueness

P. V. D. Hof, A. Damen, A. Hajdasiński, 1984 .

Approximate realization based upon an alternative to the Hankel matrix: the Page matrix

Aah Ad Damen, Ak Hajdasinski, P. V. D. Hof, 1982 .

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 .

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.

Identification and Control of a Compact Disc Mechanism using Fractional Representations

R. A. de Callafon, P. V. D. Hof, R. D. Callafon, 1994 .

Parameter identification in large-scale models for oil and gas production

Paul M.J. Van den Hof, Jan Dirk Jansen, Okko H. Bosgra, 2011 .

Identifiability: from qualitative analysis to model structure approximation

Sippe G. Douma, Paul M.J. Van den Hof, Jan Dirk Jansen, 2009 .

Model-based control of multiphase flow in subsurface oil reservoirs

Paul M.J. Van den Hof, Okko H. Bosgra, Jan Dirk Jansen, 2008 .

A generalized orthonormal basis for linear dynamical systems

P. V. D. Hof, O. Bosgra, P. Heuberger, 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

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

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

A comparison of nonlinear observers for output feedback model-based control of seeded batch crystallization processes

Paul M.J. Van den Hof, Ali Mesbah, Adrie E. M. Huesman, 2011 .

A model-based control framework for industrial batch crystallization processes

P.M.J. Van den Hof, Ali Mesbah, Adrie E. M. Huesman, 2010 .

Delft University of Technology

S. G. Douma, P. V. D. Hof, X. Bombois, 2009 .

Connecting System Identification and Robust Control by a Factorization Approach

Raymond A. de Callafon, Paul M.J. Van den Hof, P. V. D. Hof, 1997 .

Opportunities and challenges for process control in process intensification

Andrzej Stankiewicz, Paul M.J. Van den Hof, Adrie E. M. Huesman, 2012 .

An IV-based iterative linear regression algorithm with optimal Output Error properties 1

P. M. J. Van den Hof, S. G. Douma, P. V. D. Hof, 2009 .

Refined Instrumental Variable methods for closed-loop system identification

Peter C. Young, Hugues Garnier, Marion Gilson, 2009 .

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..

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.

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.

Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging

Håkan Hjalmarsson, P.M.J. Van den Hof, Xavier Bombois, 2011 .

Probabilistic model uncertainty bounding in prediction error identification based on alternative test statistics

A. J. den Dekker, X. Bombois, P. M. J. Van den Hof, 2008 .

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).

H ∞ performance analysis and distributed controller synthesis for interconnected linear systems from noisy input-state data

P. V. D. Hof, M. Lazar, T. Steentjes, 2021, 2021 60th IEEE Conference on Decision and Control (CDC).

Dynamics, load balancing and modal control of piezoelectric tube actuators

P.M.J. Van den Hof, Georg Schitter, J. van Eijk, 2012 .

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).

Observer-based correct-by-design controller synthesis pdf

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

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

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

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.

Real‐time control of a semi‐industrial fed‐batch evaporative crystallizer using different direct optimization strategies

Zoltan K. Nagy, Paul M.J. Van den Hof, Ali Mesbah, 2011 .

Real-time Dynamic Optimization of Batch Crystallization Processes

Paul M.J. Van den Hof, Ali Mesbah, Alex N. Kalbasenka, 2008 .

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).

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.

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.

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

P. V. D. Hof, Xiaodong Cheng, Shengling Shi, 2020, Autom..

Allocation of Excitation Signals for Generic Identifiability of Linear Dynamic Networks

P. V. D. Hof, Xiaodong Cheng, Shengling Shi, 2019, IEEE Transactions on Automatic Control.

Identification of physical networks through structured polynomial models pdf

Paul M.J. Van den Hof, E.M.M. Kivits, P. V. D. Hof, 2021, 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).

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).

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).

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

Mircea Lazar, Paul M.J. Van den Hof, Tom R.V. Steentjes, 2020, 2020 59th IEEE 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..

Prediction-Error Identification of LPV Systems: Present and Beyond

Paul M.J. Van den Hof, Peter S. C. Heuberger, Roland Toth, 2012 .

Identification and control - Closed-loop issues

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

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.

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).

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).

Data-driven and Model-based Verification

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

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).

Locating Nonlinearity in Mechanical Systems: A Dynamic Network Perspective

P.M.J. Van den Hof, Jean-Philippe Noël, Maarten Schoukens, 2018, Nonlinear Dynamics, Volume 1.

Identifiability of linear dynamic networks

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

Batch-to-batch model improvement for cooling crystallization

P. V. D. Hof, X. Bombois, A. Mesbah, 2015 .

Data-driven model improvement for model-based control

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

Closed-Loop Issues in System Identification

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

Instrumental Variable Methods for Closed-loop Continuous-time Model Identification

Peter C. Young, Marion Gilson, Paul M.J. Van den Hof, 2008 .

Relations between uncertainty structures in identification for robust control

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

LPV identification of high performance positioning devices

Peter S. C. Heuberger, Roland Toth, Marc van de Wal, 2011, Proceedings of the 2011 American Control Conference.

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..

An indirect method for transfer function estimation from closed loop data

Ruud J. P. Schrama, P. V. D. Hof, O. Bosgra, 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.

Identification and Control - Closed Loop Issues

Paul M.J. Van den Hof, Ruud J.P. Schrama, Ruud J. P. Schrama, 1994 .

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 .

Towards integrated design of a robust feedback controller and topography estimator for atomic force microscopy

Georg Schitter, Paul M.J. Van den Hof, Stefan Kuiper, 2011 .

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..

Identification with generalized orthonormal basis functions - statistical analysis and error bounds

József Bokor, Peter S. C. Heuberger, P. V. D. Hof, 1994 .

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

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

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.

Instrumental variable methods for continuous-time model identification in closed-loop

M. Gilson, H. Garnier, P. Van den Hof, 2004, Proceedings of the 2004 American Control Conference.

Closed-loop system identification via a tailor-made IV method

M. Gilson, P. Van den Hof, P. V. D. Hof, 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

System identification with generalized orthonormal basis functions

P. V. D. Hof, P. Heuberger, J. Bokor, 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

Modelling Linear Dynamical Systems through Generalized Orthonormal Basis Functions

Okko H. Bosgra, Peter S. C. Heuberger, P. V. D. Hof, 1993 .

A Necessary Condition for Network Identifiability With Partial Excitation and Measurement

Ioannis Lestas, Paul M.J. Van den Hof, Shengling Shi, 2021, IEEE Transactions on Automatic Control.

Accelerating simulations of computationally intensive first principle models using accurate quasi-linear parameter varying models

Xavier Bombois, Paul M.J. Van den Hof, R. Bos, 2009 .

Accelerating simulations of first principle models of complex industrial systems using quasi linear parameter varying models

P.M.J. Van den Hof, R. Bos, X. Bombois, 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

Accelerating large-scale non-linear models for monitoring and control using spatial and temporal correlations

X. Bombois, P. Van den Hof, R. Bos, 2004, Proceedings of the 2004 American Control Conference.

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.

Least costly identification experiment for control

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

The Behavioral Approach to Linear Parameter-Varying Systems

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

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

P. V. D. Hof, M. Lazar, T. Steentjes, 2022, IFAC-PapersOnLine.

Indirect Force measurement of Micromilling with an Active Magnetic Bearing spindle

A. M. Hoogstrate, H. H. Langen, R. S. Blom, 2007 .

Frequency domain curve fitting with maximum amplitude criterion and guaranteed stability

Paul M.J. Van den Hof, Richard G. Hakvoort, P. V. D. Hof, 1994 .

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..

Trajectory planning and trajectory tracking for a small-scale helicopter in autorotation

Xavier Bombois, Skander Taamallah, Paul M.J. Van den Hof, 2017 .

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).

Experiment design for robust control: Why do more work than is needed?

Xavier Bombois, Gérard Scorletti, P.M.J. Van den Hof, 2006 .

Minimal partial realization from generalized orthonormal basis function expansions

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

Minimal partial realization from orthonormal basis function expansions

J. Bokor, P.M.J. Van den Hof, Z. Szabo, 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

A general transform theory of rational orthonormal basis function expansions

P.M.J. Van den Hof, P. V. D. Hof, P. Heuberger, 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

The Hambo Transform: A Signal and System Transform Induced by Generalized Orthonormal Basis Functions

Paul M.J. Van den Hof, Peter S. C. Heuberger, P. V. D. Hof, 1996 .

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 .

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..

Asymptotically optimal orthonormal basis functions for LPV system identification

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

Consistent parameter bounding identification for linearly parametrized model sets

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

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..

Learning local modules in dynamic networks without prior topology information

K. R. Ramaswamy, P. V. D. Hof, V. C. Rajagopal, 2021, 2021 60th IEEE Conference on Decision and Control (CDC).

A frequency domain approach for local module identification in dynamic networks pdf

Johan Schoukens, Paul M.J. Van den Hof, Karthik R. Ramaswamy, 2021, Autom..

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).

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).

A Local Direct Method for Module Identification in Dynamic Networks With Correlated Noise pdf

Paul M.J. Van den Hof, Karthik R. Ramaswamy, K. R. Ramaswamy, 2019, IEEE Transactions on Automatic 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).

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).

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).

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).

Identification in dynamic networks

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

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).

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.

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).

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.

Least-costly experiment design for uni-parametric linear models: An analytical approach

Marco Forgione, P.M.J. Van den Hof, Xavier Bombois, 2015, 2015 European Control Conference (ECC).

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

P. V. D. Hof, X. Bombois, A. Mesbaha, 2015, Int. J. Control.

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.

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..

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).

Dynamic network structure identification with prediction error methods - basic examples

Xavier Bombois, Paul M.J. Van den Hof, Arne G. Dankers, 2012 .

Experiment Design for Closed-loop Performance Diagnosis

Xavier Bombois, Ali Mesbah, Paul M.J. Van den Hof, 2012 .

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.

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.

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.

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.

Structural Identifiability of Grid Block and Geological Parameters in Reservoir Simulation Models

Jan Dirk Jansen, Okko H. Bosgra, P. V. D. Hof, 2008 .

Identification of Parameters in Large Scale Physical Model Structures, for the Purpose of Model-Based Operations

Sippe G. Douma, Paul M.J. Van den Hof, Jorn F. M. Van Doren, 2009 .

DEGREES OF FREEDOM ANALYSIS OF ECONOMIC DYNAMIC OPTIMAL PLANTWIDE OPERATION

P.M.J. Van den Hof, Okko H. Bosgra, Adrie E. M. Huesman, 2007 .

Filtering And Parametrization Issues In Feedback Relevant Identification Based On Fractional Model R

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