Koen Tiels

According to our database, Koen Tiels authored at least 42 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Memory-Element-Based Hysteresis: Identification and Compensation of a Piezoelectric Actuator.

Nard Strijbosch, Koen Tiels, Tom Oomen

IEEE Trans. Control. Syst. Technol., November, 2023

Learning low-dimensional separable decompositions of MIMO non-linear systems.

Pawel Wachel, Koen Tiels, Maciej Filinski

Int. J. Control, April, 2023

A Wavelet-Based Approach to FRF Identification From Incomplete Data.

Nic Dirkx, Koen Tiels, Tom Oomen

IEEE Trans. Instrum. Meas., 2023

Neural oscillators for magnetic hysteresis modeling.

Abhishek Chandra, Taniya Kapoor, Bram Daniels, Mitrofan Curti, Koen Tiels, Daniel M. Tartakovsky, Elena A. Lomonova

CoRR, 2023

Identifying Lebesgue-sampled Continuous-time Impulse Response Models: A Kernel-based Approach.

Rodrigo A. González, Koen Tiels, Tom Oomen

CoRR, 2023

Kernel-based identification using Lebesgue-sampled data.

Rodrigo A. González, Koen Tiels, Tom Oomen

CoRR, 2023

Discovering Sparse Hysteresis Models: A Data-driven Study for Piezoelectric Materials and Perspectives on Magnetic Hysteresis.

Abhishek Chandra, Bram Daniels, Mitrofan Curti, Koen Tiels, Elena A. Lomonova, Daniel M. Tartakovsky

CoRR, 2023

A Computationally Lightweight Safe Learning Algorithm.

Dominik Baumann, Krzysztof Kowalczyk, Koen Tiels, Pawel Wachel

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Iterative Robust Experiment Design for MIMO System Identification via the S-Lemma.

Nic Dirkx, Koen Tiels, Tom Oomen

Proceedings of the IEEE Conference on Control Technology and Applications, 2023

2022

Hysteresis Feedforward Compensation: A Direct Tuning Approach Using Hybrid-MEM-Elements.

Nard Strijbosch, Koen Tiels, Tom Oomen

IEEE Control. Syst. Lett., 2022

Decoupling multivariate functions using a nonparametric filtered tensor decomposition.

Jan Decuyper, Koen Tiels, Siep Weiland, Mark C. Runacres, Johan Schoukens

CoRR, 2022

Physics-informed neural networks for modelling anisotropic and bi-anisotropic electromagnetic constitutive laws through indirect data.

Abhishek Chandra, Mitrofan Curti, Koen Tiels, Elena A. Lomonova, Daniel M. Tartakovsky

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

2021

PNLSS Toolbox 1.0.

Jan Decuyper, Koen Tiels, Johan Schoukens

CoRR, 2021

Decoupling multivariate functions using a non-parametric Filtered CPD approach.

Jan Decuyper, Koen Tiels, Siep Weiland, Johan Schoukens

CoRR, 2021

Low-Dimensional Decompositions for Nonlinear Finite Impulse Response Modeling.

Maciej Filinski, Pawel Wachel, Koen Tiels

Proceedings of the Computational Science - ICCS 2021, 2021

2020

A nonlinear model of vortex-induced forces on an oscillating cylinder in a fluid flow.

Jan Decuyper, Tim De Troyer, Koen Tiels, Johan Schoukens, Mark C. Runacres

CoRR, 2020

Retrieving highly structured models starting from black-box nonlinear state-space models using polynomial decoupling.

Jan Decuyper, Koen Tiels, Mark C. Runacres, Johan Schoukens

CoRR, 2020

On the smoothness of nonlinear system identification.

Antônio H. Ribeiro, Koen Tiels, Jack Umenberger, Thomas B. Schön, Luis Antonio Aguirre

Autom., 2020

Beyond exploding and vanishing gradients: analysing RNN training using attractors and smoothness.

Antônio H. Ribeiro, Koen Tiels, Luis Antonio Aguirre, Thomas B. Schön

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Decoupling Multivariate Polynomials for Nonlinear State-Space Models.

Jan Decuyper, Philippe Dreesen, Johan Schoukens, Mark Runacres, Koen Tiels

IEEE Control. Syst. Lett., 2019

The trade-off between long-term memory and smoothness for recurrent networks.

Antônio H. Ribeiro, Koen Tiels, Luis Antonio Aguirre, Thomas B. Schön

CoRR, 2019

Sampled-data adaptive observer for state-affine systems with uncertain output equation.

Tarek Ahmed-Ali, Koen Tiels, Maarten Schoukens, Fouad Giri

Autom., 2019

Deep Convolutional Networks in System Identification.

Carl R. Andersson, Antônio H. Ribeiro, Koen Tiels, Niklas Wahlström, Thomas B. Schön

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018

Hammerstein system identification through best linear approximation inversion and regularisation.

Ricardo Castro-Garcia, Koen Tiels, Oscar Mauricio Agudelo, Johan A. K. Suykens

Int. J. Control, 2018

Data driven discrete-time parsimonious identification of a nonlinear state-space model for a weakly nonlinear system with short data record.

Rishi Relan, Koen Tiels, Anna Marconato, Philippe Dreesen, Johan Schoukens

CoRR, 2018

Nonlinear state-space modelling of the kinematics of an oscillating circular cylinder in a fluid flow.

Jan Decuyper, Tim De Troyer, Mark Runacres, Koen Tiels, Johan Schoukens

CoRR, 2018

Comparison of several data-driven nonlinear system identification methods on a simplified glucoregulatory system example.

Anna Marconato, Maarten Schoukens, Koen Tiels, Widanalage Dhammika Widanage, Amjad Abu-Rmileh, Johan Schoukens

CoRR, 2018

2017

A Local Polynomial Approach to Nonparametric Estimation of the Best Linear Approximation of Lithium-Ion Battery From Multiple Datasets.

Rishi Relan, Koen Tiels, Jean-Marc Timmermans, Johan Schoukens

IEEE Control. Syst. Lett., 2017

Parameter reduction in nonlinear state-space identification of hysteresis.

Alireza Fakhrizadeh Esfahani, Philippe Dreesen, Koen Tiels, Jean-Philippe Noël, Johan Schoukens

CoRR, 2017

Identification of block-oriented nonlinear systems starting from linear approximations: A survey.

Maarten Schoukens, Koen Tiels

Autom., 2017

Nonlinear system identification: Finding structure in nonlinear black-box models.

Philippe Dreesen, Koen Tiels, Mariya Ishteva, Johan Schoukens

Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2016

Identification of Nonlinear Block-Oriented Systems starting from Linear Approximations: A Survey.

Maarten Schoukens, Koen Tiels

CoRR, 2016

Hammerstein system identification using LS-SVM and steady state time response.

Ricardo Castro-Garcia, Oscar Mauricio Agudelo, Koen Tiels, Johan A. K. Suykens

Proceedings of the 15th European Control Conference, 2016

2015

Initial estimates for Wiener-Hammerstein models using phase-coupled multisines.

Koen Tiels, Maarten Schoukens, Johan Schoukens

Autom., 2015

Structure discrimination in block-oriented models using linear approximations: A theoretic framework.

Johan Schoukens, Rik Pintelon, Yves Rolain, Maarten Schoukens, Koen Tiels, Laurent Vanbeylen, Anne Van Mulders, Gerd Vandersteen

Autom., 2015

Decoupling static nonlinearities in a parallel Wiener-Hammerstein system: A first-order approach.

Philippe Dreesen, Maarten Schoukens, Koen Tiels, Johan Schoukens

Proceedings of the 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2015

Incorporating Best Linear Approximation within LS-SVM-based Hammerstein System Identification.

Ricardo Castro-Garcia, Koen Tiels, Johan Schoukens, Johan A. K. Suykens

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2014

Wiener system identification with generalized orthonormal basis functions.

Koen Tiels, Johan Schoukens

Autom., 2014

System identification in a real world.

Johan Schoukens, Anna Marconato, Rik Pintelon, Yves Rolain, Maarten Schoukens, Koen Tiels, Laurent Vanbeylen, Gerd Vandersteen, Anne Van Mulders

Proceedings of the IEEE 13th International Workshop on Advanced Motion Control, 2014

2013

From coupled to decoupled polynomial representations in parallel Wiener-Hammerstein models.

Koen Tiels, Johan Schoukens

Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Iterative Update of the Pole Locations in a Wiener-Schetzen Model.

Koen Tiels, Johan Schoukens

Proceedings of the 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, 2013

2011

Identifying a Wiener system using a variant of the Wiener G-Functionals.

Koen Tiels, Johan Schoukens

Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011