# History

This page collects the abstracts and presentations that were part of the different editions of the Workshop on Nonlinear System Identification Benchmarks and the results of recent invited sessions based upon the benchmarks featured on this website. You can find the keynotes and regular talks of the past workshops, and the list of invited sessions below.

Would you want to feature additional material (slides, code, toolbox, ...)? Please contact us and we will include your research material on this webpage!

## Workshop History

### 2024 Workshop

The eighth edition of the Workshop on Nonlinear System Identification Benchmarks was held in Lugano, Switzerland, April 24-26 2024 organized by Dario Piga and Marco Forgione. It featured the talks that are listed below. The complete book of abstracts of the 2024 Workshop on Nonlinear System Identification Benchmarks can be found here.

### Keynote Speakers:

Mario Sznaier, Northeastern University, USA

Keynote: Why do we need "control" in control oriented learning?Roland Tóth, Eindhoven University of Technology, Netherlands & Institute for Computer Science and Control (Sztaki), Hungary

Keynote: Data-driven surrogate modeling: The Tale of Linear Parameter-Varying Methods. slidesAlberto Bemporad, IMT Lucca, Italy

Keynote: Quasi-Newton Methods for Learning Nonlinear State-Space Models. slides, codeMelanie Zeilinger, ETH Zurich, Switzerland

Keynote: Learning Models for Control and Estimation

### Regular Talks:

Max D. Champneys, Gerben I. Beintema, Roland Tóth, Maarten Schoukens, and Timothy J. Rogers - Baselines for Nonlinear Benchmarks, Workshop on Nonlinear System Identification Benchmarks, 2024. slides, arXiv, code

Aurelio Raffa Ugolini, Valentina Breschi, Andrea Manzoni, and Mara Tanelli - SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study, Workshop on Nonlinear System Identification Benchmarks, 2024. slides, arXiv, code

Prabhu Vijayan, Mariya Ishteva, John Lataire, and Philippe Dreesen - PNLSS modelling and estimation using prior-incorporated Volterra kernel: A Wiener-Hammerstein case study, Workshop on Nonlinear System Identification Benchmarks, 2024. slides

Max Heinz Herkersdorf - Excitation Signal Design for Hysteretic Processes, Workshop on Nonlinear System Identification Benchmarks, 2024. slides, code

Hermann Klein and Oliver Nelles - Identification of Gray-Box Hysteresis State Space Models, Workshop on Nonlinear System Identification Benchmarks, 2024. slides

Daniel Frank, Tobias Holicki, Steffen Staab, and Carsten W. Scherer - Constrained residual RNN for nonlinear system identification, Workshop on Nonlinear System Identification Benchmarks, 2024. slides, code

Jan Hoekstra, Chris Verhoek, Roland Tóth, and Maarten Schoukens - Learning-based model augmentation for cascaded tanks, Workshop on Nonlinear System Identification Benchmarks, 2024. slides, arXiv

Ankush Chakrabarty, Gordon Wichern, and Abraham P. Vinod - Meta-Learning for Online Adaptive Neural System Identification, Workshop on Nonlinear System Identification Benchmarks, 2024. slides

Matteo Rufolo, Filippo Pura, Dario Piga, and Marco Forgione - In-context learning for model-free system identification, Workshop on Nonlinear System Identification Benchmarks, 2024. slides, arXiv, code

Sergio M. Vanegas A., Lasse Lensu, and Fredy O. Ruiz P. - Multi-Window Autoformer for Dynamic Systems Modelling, Workshop on Nonlinear System Identification Benchmarks, 2024. slides, code

Sarvin Moradi, Gerben I. Beintema, Nick O. Jaensson, Roland Tóth, and Maarten Schoukens - Output error port-Hamiltonian neural networks: Cascaded tanks system with overflow, Workshop on Nonlinear System Identification Benchmarks, 2024. slides

Gulliver Van Essche, Jan Decuyper, Tim de Troyer, and Mark C. Runacres - Long Short-Term Memory (LSTM) neural network models for the wake of an oscillating cylinder, Workshop on Nonlinear System Identification Benchmarks, 2024. slides

Gerben I. Beintema, Roland Tóth, and Maarten Schoukens - Effective State-Space Models Estimation for 2D Flows Using Convolutional Neural Networks in a SUBNET Approach, Workshop on Nonlinear System Identification Benchmarks, 2024. slides, slides (with animations), paper, code

Daniel O.M. Weber and Clemens Gühmann - Fast Non-Autoregressive Multi-Step-Ahead Prediction with Recurrent Neural Networks, Workshop on Nonlinear System Identification Benchmarks, 2024.

Antonio Fazzi - Nonlinear Systems Identification in the behavioral setting, Workshop on Nonlinear System Identification Benchmarks, 2024.

Matteo Scandella and Mirko Mazzoleni - Incremental ISS stable model for the coupled electric drives, Workshop on Nonlinear System Identification Benchmarks, 2024. slides

Yuhan Liu, Roland Tóth, and Maarten Schoukens - Weighted Neural Networks Regularization for State-Space Model Augmentation, Workshop on Nonlinear System Identification Benchmarks, 2024. slides, arXiv

Marco Forgione, Manas Mejari, and Dario Piga - Model order reduction of deep structured state-space models: a system-theoretic approach, Workshop on Nonlinear System Identification Benchmarks, 2024. slides, arXiv, code

Merijn Floren, Jean-Philippe Noël, and Jan Swevers - Robust identification of nonlinear block-oriented systems: application to the F16 benchmark, Workshop on Nonlinear System Identification Benchmarks, 2024. slides

Cesare Donati, Martina Mammarella, Fabrizio Dabbene, Carlo Novara, and Constantino Lagoa - A structured approach to multi-step and physics-based system identification, Workshop on Nonlinear System Identification Benchmarks, 2024. (presented by Mattia Boggio), slides

### 2023 Workshop

The seventh edition of the Workshop on Nonlinear System Identification Benchmarks was held in Eindhoven, The Netherlands, April 19-21 2023. It featured the talks that are listed below. The complete book of abstracts of the 2023 Workshop on Nonlinear System Identification Benchmarks can be found here.

### Keynote Speakers:

Dario Piga, IDSIA - Dalle Molle Institute for Artificial Intelligence Research, Switzerland

Keynote: Deep learning for system identification, and viceversa. slidesWouter Kouw, Eindhoven University of Technology, The Netherlands

Keynote: Variational Bayesian Inference for System Identification. slides, codeSteve Brunton, University of Washington, USA

Keynote: Machine Learning for Scientific Discovery, with Examples in Fluid MechanicsOlga Fink, Swiss Federal Institute of Technology Lausanne, Switzerland

Keynote: Fusing physics-based and deep learning algorithms for fault diagnostics and prognostics. slides

### Regular Talks:

L. Frascati and A. Bemporad - Nonlinear systems identification with automatic state/model size reduction using RESNETs and Group Lasso, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

T. Nagel and M.F. Huber - Kalman-Bucy-Informed Neural Network for System Identification, Workshop on Nonlinear System Identification Benchmarks, 2023.

S. Moradi, G.I. Beintema, N. Jaensson, R. Tóth and M. Schoukens - Output error port Hamiltonian neural networks: a Silverbox case example, Workshop on Nonlinear System Identification Benchmarks, 2023.

F. Gismondi, C. Verhoek, G.I. Beintema, M. Schoukens and R. Tóth - System modeling through LPV sub-space encoder networks, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

M.D. Champneys, M.J. Jones and T.J. Rogers - The benefit of hindsight: Does lag selection matter?, Workshop on Nonlinear System Identification Benchmarks, 2023.

M. Runacres, J. Decuyper, T. De Troyer, J. Foster and J. Schoukens - Canonical systems for unsteady fluid mechanics: a new family of nonlinear benchmarks, Workshop on Nonlinear System Identification Benchmarks, 2023.

A. Pavsek, M. Horvat and J. Kocijan - Noise dependence of dynamical and statistical properties of surrogate SINDy models, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

D. Joedicke - Comparison of different approaches for parameter optimization to predict the behaviour of dynamical systems using exhaustive search, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

H.-L. Wei - Transparent and Parsimonious Nonlinear Model Identification Using a Majority Voting Ensemble Scheme: The Case of the Cascaded Tanks Benchmark, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

G.I. Beintema, R. Tóth and M. Schoukens - Identification of Stochastic Systems with Meta-state-space Models, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

M. Floren, J.-P. Noël and J. Swevers - Data-driven state-space identification of nonlinear feedback systems, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

A. Ali Shahid, M. Forgione, M. Gallieri, L. Roveda and D. Piga - Robotics Benchmark on Transfer Learning: a Human-Robot Collaboration Use Case, Workshop on Nonlinear System Identification Benchmarks, 2023.

A. Bemporad - Training recurrent neural-network models on the industrial robot dataset under ℓ1-regularization, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

A. Retzler, R. Tóth , G.I. Beintema, J.-P. Noël , M. Schoukens, J. Weigand, Z. Kollár and J. Swevers - Identifying a simulation model of an industrial robot, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

B. Renczes, J. Decuyper and M. Schoukens - Increasing the Interpretability of State-space Neural Networks by Means of Compression and Fourier-based Function Decoupling, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

M. Forgione and D. Piga - Uncertainty quantification of neural state-space models, Workshop on Nonlinear System Identification Benchmarks, 2023. slides

### Special Session for Johan Schoukens' 65th Birthday:

A special session was organized during this workshop on the occasion of Johan Schoukens’ 65th birthday to celebrate over 40 years of research conducted by Johan throughout his academic career. Beyond his large contributions to frequency-domain and nonlinear system identification, Johan has provided crucial support in setting up this workshop series and benchmark initiative, and he also played a key role in the academic careers of the workshop organizers (see intro slides).

During this session, a retrospect on 40+ years of system identification research and personal collaborations will be provided by close colleagues of Johan:

Paul Van den Hof, Eindhoven University of Technology, The Netherlands. slides

Tadeusz Dobrowiecki, Budapest University of Technology and Economics, Hungary. slides

Tom Oomen, Eindhoven University of Technology, The Netherlands. slides

Mark Runacres, Vrije Universiteit Brussel, Belgium. slides

Bart De Moor, KU Leuven, Belgium. slides

Group picture of the participants on the last day of the 2023 NSIB Workshop:

### 2022 Workshop

The sixth edition of the Workshop on Nonlinear System Identification Benchmarks was held in Leuven, Belgium, April 25-27 2022. It featured the talks that are listed below. The complete book of abstracts of the 2022 Workshop on Nonlinear System Identification Benchmarks can be found here.

### Keynote Speakers:

Håkan Hjalmarsson, Royal Institute of Technology (KTH), Sweden

Keynote: Identification of nonlinear stochastic differential-algebraic equation models, slidesJuš Kocijan, Jožef Stefan Institute, Slovenia

Keynote: Simulation of autoregressive Gaussian-process models, slidesDhammika Widanage, University of Warwick, UK

Keynote: Nonlinear system identification of battery dynamics and future directions, slides, GitHubKim Batselier, Delft University of Technology, The Netherlands

Keynote: Tensor-based kernel methods for nonlinear system identification, slides

### Regular Talks:

G.I. Beintema, M. Schoukens and R. Tóth, Continuous-time model identification using deep subspace encoders, Workshop on Nonlinear System Identification Benchmarks, 2022. slides, paper, code, toolbox

A. Hache, M. Thieffry, M. Yagoubi and P. Chevrel, Identification of Control-Oriented Descriptor Neural-State-Space Models, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

C. Illg and O. Nelles, Regularized Local FIR Model Networks for Enhanced Physical Interpretability, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

J. Weigand, M. Deflorian and M. Ruskowski, Input-to-State Stability for System Identification with Continuous-Time Runge-Kutta Neural Networks, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

F. Shakib, N. Vervaet, A. Pogromsky, A. Pavlov and N. van de Wouw, Fast identification of Lur’e-type models with stability guarantees, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

M.O. Ajeni and W.P. Heath, Parameter Estimation of a Nonlinear State Space Model using Particle Filtering and Smoothing, Workshop on Nonlinear System Identification Benchmarks, 2022.

T. Li, Multiple local particle filter for high-dimensional system identification, Workshop on Nonlinear System Identification Benchmarks, 2022.

J. Weigand, J. Götz, J. Ulmen and M. Ruskowski, Dataset and Baseline for an Industrial Robot Identification Benchmark, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

J.D. Longbottom, M.D. Champneys, E.J. Cross and T.J. Rogers, Identifying the Bouc-Wen System in Continuous Time: A Probabilistic ODE Solver Approach, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

H. Zhou and W. Pan, Sparse Bayesian Deep Learning for Dynamic System Identification, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

W. Kouw, A. Podusenko and M. Schoukens, Variational Bayes for online polynomial NARMAX identification, Workshop on Nonlinear System Identification Benchmarks, 2022. slides, code & toolbox

K. Vlachas, T. Simpson, A. Garland, C. Martinez and E. Chatzi, VAE Boosted Parametric Reduced Order Modelling, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

L.C. Iacob, G.I. Beintema, M. Schoukens and R. Tóth, Model Structure Selection for the Identification of Nonlinear Systems Using the Koopman Operator, Workshop on Nonlinear System Identification Benchmarks, 2022. slides, toolbox

A. Retzler, J. Swevers, J. Gillis and Z. Kollar, Nlgreyfast: toolbox for identification of nonlinear state-space grey-box models, Workshop on Nonlinear System Identification Benchmarks, 2022. slides, video, code

S. Pirrera, Set-Membership identification approach to nonlinear block-structured systems: Silverbox, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

J. Decuyper and M. Schoukens, Reducing state-space neural networks using function decoupling, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

L. Glass, W. Hilali and O. Nelles, Hybrid System Identification of a Wiener-Hammerstein Process using Rectified Linear Unit based Local Linear Model Tree, Workshop on Nonlinear System Identification Benchmarks, 2022. slides

A. Montanari, F. Lamoline and J. Gonçalves, Identifiability of differential-algebraic and closed-loop systems: A case study of the electro-mechanical positioning system, Workshop on Nonlinear System Identification Benchmarks, 2022. slides, code

Group picture of (most of) the participants of the 2022 NSIB Workshop:

### 2021 Workshop

The fifth edition of the Workshop on Nonlinear System Identification Benchmarks was an online edition, taking place on April 22-23 2021. This edition was sponsored by Siemens. It featured the talks that are listed below. The complete book of abstracts of the 2021 Workshop on Nonlinear System Identification Benchmarks can be found here.

### Regular Talks:

M. Forgione, M. Mejari, D. Piga, dynoNet: A neural network architecture for learning dynamical systems, Workshop on Nonlinear System Identification Benchmarks, 2021. slides, Python toolbox: dynoNet, Python toolbox: tansfer functions, full paper

G.I. Beintema, R. Tóth, M. Schoukens, Nonlinear state-space identification using sub-space encoders: A Wiener-Hammerstein case-study, Workshop on Nonlinear System Identification Benchmarks, 2021. slides, Python toolbox: deepSI, WH code, video encoder code, full paper

T. Decker, H. Patel, M. Schussler, O. Nelles, Neural Networks with different Dynamics Realizations for the Bouc-Wen Benchmark Problem, Workshop on Nonlinear System Identification Benchmarks, 2021. slides, extended abstract

J.N. Hendriks, F.K. Gustafsson, A.H. Ribeiro, A.G. Wills, T.B. Schön, Deep Energy-Based NARX Models, Workshop on Nonlinear System Identification Benchmarks, 2021. slides, code, full paper

T.J. Rogers, T. Friis, K. Worden, E.J. Cross, Gaussian Process Latent Nonlinear Restoring Force Identification of The Silverbox, Workshop on Nonlinear System Identification Benchmarks, 2021. slides

K. Vlachas, K. Agathos, K. Tatsis, A.R. Brink, E.N. Chatzi, Two-story frame with Bouc-Wen hysteretic links as a multi-degree of freedom nonlinear response simulator, Workshop on Nonlinear System Identification Benchmarks, 2021. extended abstract

M. Elkafafy, L. Lugo, L. Signori, B. Cornelis, T. Geluk, K. Janssens, Detection, understanding, and localization of nonlinearities in a vehicle suspension system, Workshop on Nonlinear System Identification Benchmarks, 2021. slides

J. Schoukens, J. Decuyper, A bird’s eye perspective on decoupling in Black Box Nonlinear System Identification, Workshop on Nonlinear System Identification Benchmarks, 2021. slides, extended abstract

P.Z. Csurcsia, J. Decuyper, J. Schoukens, T. De Troyer, Empirical study on decoupling PNLSS models illustrated on F16, Workshop on Nonlinear System Identification Benchmarks, 2021. slides

R. Karagoz, K. Batselier, Nonlinear system identification with regularized Tensor Network B-splines, Workshop on Nonlinear System Identification Benchmarks, 2021. slides, extended abstract, code

E.J. Cross, M.R. Jones, W. Lin, R. Nayek, D.J. Pitchforth, T.J. Rogers, Grey-box benchmarks system identification with Gaussian processes, Workshop on Nonlinear System Identification Benchmarks, 2021.

L.C. Iacob, G.I. Beintema, M. Schoukens, R. Tóth, Deep Identification of Nonlinear Systems in Koopman Form, Workshop on Nonlinear System Identification Benchmarks, 2021. slides, Python toolbox: deepSI

A.H. Ribeiro, J.N. Hendriks, A.G. Wills, T.B. Schön, Beyond Occam’s Razor in System Identification: Double-Descent when Modeling Dynamics, Workshop on Nonlinear System Identification Benchmarks, 2021. slides, code, full paper

### 2019 Workshop

The fourth edition of the Workshop on Nonlinear System Identification Benchmarks was held in Eindhoven, The Netherlands, April 10-12 2019. This edition was sponsored by Siemens. It featured the talks that are listed below. The complete book of abstracts of the 2019 Workshop on Nonlinear System Identification Benchmarks can be found here.

### Keynote Speakers:

Gianluigi Pillonetto, University of Padova, Italy

Keynote: Regularization networks for system identification, slidesOliver Nelles, University of Siegen, Germany

Keynote: Challenges in nonlinear system identification, slidesFredrik Lindsten, Linkoping University, Sweden

Keynote: Learning dynamical systems with particle stochastic approximation EM, slidesElizabeth Cross, The University of Sheffield, United Kingdom

Keynote: Grey-Box models for structural dynamics, slides

### Regular Talks:

M. Schüssler, T.O. Heinz and O. Nelles, Local Model State Space Networks for Hysteresis Identification, Workshop on Nonlinear System Identification Benchmarks, 2019.

J. Decuyper, K. Tiels and J. Schoukens, Reducing nonlinear state-space models through polynomial Decoupling, Workshop on Nonlinear System Identification Benchmarks, 2019. slides

K. Karami and D. Westwick, Polynomial Constrained Factoring in P-NARX Identification, Workshop on Nonlinear System Identification Benchmarks, 2019. slides

A.C. Schouten, M.P. Vlaar, T. Solis-Escalante, Y. Yang and F.C.T. van der Helm, Cortical responses evoked by wrist joint manipulation, Workshop on Nonlinear System Identification Benchmarks, 2019. slides

Z. Tuza and G.-B. Stan, Identifying Evoked Cortical Responses Using Block-Sparse Bayesian Learning, Workshop on Nonlinear System Identification Benchmarks, 2019.

R.G. Junker and R. Relan, Continuous-time Stochastic Grey-box Model of the Nonlinear Feedback System based on Residual Analysis, Workshop on Nonlinear System Identification Benchmarks, 2019. slides

T.J. Rogers and E.J. Cross, Particle MCMC Approaches to the Silverbox Benchmark, Workshop on Nonlinear System Identification Benchmarks, 2019.

P. Gardner and R.J. Barthorpe, Estimation of Model Discrepancy using a Bayesian History Matching and Importance Sampling Approach, Workshop on Nonlinear System Identification Benchmarks, 2019.

K. Tiels and J. Decuyper, PNLSS 1.0, Workshop on Nonlinear System Identification Benchmarks, 2019. slides, Matlab demo

T. Krivec and L. Žnidarič, Sparse Gaussian Process Regression for System Identification, Workshop on Nonlinear System Identification Benchmarks, 2019.

H. Zhou and W. Pan, Sparse Bayesian Deep Neural Networks for Nonlinear System Identification, Workshop on Nonlinear System Identification Benchmarks, 2019.

A.H. Ribeiro, C. Andersson, K. Tiels, N. Wahlström and T.B. Schön, Deep Convolutional Networks are Useful in System Identification, Workshop on Nonlinear System Identification Benchmarks, 2019. slides

B. Peeters, P.Z. Csurcsia, Structural nonlinearities – an industrial view, Workshop on Nonlinear System Identification Benchmarks, 2019.

R. Fuentes, K. Worden and E.J. Cross, Equation Discovery using Sparse Bayesian Learning, applied to the Electro-Mechanical Positioning System, Workshop on Nonlinear System Identification Benchmarks, 2019.

D. Khandelwal, M. Schoukens and R. Tóth, Automating System Identification Using Grammar and Genetic Programming, Workshop on Nonlinear System Identification Benchmarks, 2019. slides

K. Tatsis, T. Simpson, E. Chatzi, Bayesian and Genetic Methods for Model Selection of Greybox Modelling on the Silverbox, Workshop on Nonlinear System Identification Benchmarks, 2019.

T.O. Heinz and O. Nelles, LMN-Tool: Matlab-Toolbox for Local Model Networks, Workshop on Nonlinear System Identification Benchmarks, 2019.

M. Schoukens and R. Tóth, Identification of Nonlinear LFR Systems starting from the Best Linear Approximation, Workshop on Nonlinear System Identification Benchmarks, 2019. slides

K. Batselier, Lifting the curse of dimensionality in nonlinear system identification with tensor networks, Workshop on Nonlinear System Identification Benchmarks, 2019. slides

### 2018 Workshop

The third edition of the Workshop on Nonlinear System Identification Benchmarks was held in Liege, Belgium, April 11-13 2018. This edition was sponsored by the University of Liege and Siemens. It featured the talks that are listed below. The complete book of abstracts of the 2018 Workshop on Nonlinear System Identification Benchmarks can be found here.

### Keynote Speakers:

Eleni Chatzi, ETH Zürich, Switzerland

Keynote: Data-Driven Assessment of Engineered Systems: Beyond LTI, slidesAlfred Schouten TU Delft, The Netherlands

Keynote: Nonlinear cortical responses in EEG evoked by continuous wrist manipulations, slidesJohan Suykens, KU Leuven, Belgium

Keynote: Function estimation, model representations and nonlinear system identification, slidesPeter Young, University of Lancaster, UK

Keynote: State-Dependent Parameter (SDP) Nonlinear Models and a Hydrological Identification Benchmark, slides, demo and background materialJorge Goncalves, University of Luxembourg, Luxembourg

Keynote: Challenges in system identification of biochemical systems, slides

### Regular Talks:

T.O. Heinz, T. Münker and O. Nelles, Identification of Systems with Hysteretic Behavior Using NOBF Local Model Networks, Workshop on Nonlinear System Identification Benchmarks, 2018.

K. Karami, D. Westwick and J. Schoukens, Identification of Decoupled Polynomial NARX Models using Simulation Error Minimization, Workshop on Nonlinear System Identification Benchmarks, 2018. slides

J. Decuyper, A. Fakhrizadeh Esfahani, K. Tiels and J. Schoukens, Retrieving highly structured models starting from a black box state-space model: a case study on the Bouc-Wen hysteresis model, Workshop on Nonlinear System Identification Benchmarks, 2018. slides

B. Peeters, P.Z Csurcsia and J. Schoukens, The use of exotic multisines in MIMO structural dynamics and acoustic applications, Workshop on Nonlinear System Identification Benchmarks, 2018. slides

M. Perne and M. Stepančič, Regressor selection using Lipschitz quotients on the F-16 aircraft benchmark, Workshop on Nonlinear System Identification Benchmarks, 2018. slides, Matlab code

M. Mazzoleni, M. Scandella and F. Previdi, Kernel manifold regression for the coupled electric drives dataset, Workshop on Nonlinear System Identification Benchmarks, 2018. slides, Matlab code

M.R.-H. Abdalmoaty and H. Hjalmarsson, Application of a Linear PEM estimator to a stochastic Wiener-Hammerstein Benchmark Problem, Workshop on Nonlinear System Identification Benchmarks, 2018.

G. Birpoutsoukis and M. Schoukens, From the Volterra series to a Wiener-Hammerstein model, Workshop on Nonlinear System Identification Benchmarks, 2018.

M. Stepančič, M. Perne and J. Kocijan, Regularised NFIR identification with Gaussian process model, Workshop on Nonlinear System Identification Benchmarks, 2018.

D. Bouvier, T. Hélie and D. Roze, Phase-based homogeneous order separation for improving Volterra series identification, Workshop on Nonlinear System Identification Benchmarks, 2018. slides, Python Toolbox

N. Simidjievski, L. Todorovski, S. Džeroski, and J. Kocijan, Nonlinear System Identification with Equation Discovery, Workshop on Nonlinear System Identification Benchmarks, 2018.

P.Z. Csurcsia, J. Schoukens and B. Peeters, Nonparametric Approximation of the Nonlinear SilverBox Data: a Linear Time-varying Approach, Workshop on Nonlinear System Identification Benchmarks, 2018.

J. Schoukens, Simulation and Prediction Errors in the Presence of Model Errors: a Case Study on the Silverbox, Workshop on Nonlinear System Identification Benchmarks, 2018.

R. Hostettler, F. Tronarp and S. Särkkä, Nonparametric Drift Model for Stochastic Differential Equations, Workshop on Nonlinear System Identification Benchmarks, 2018. slides

M. Schoukens and R. Tóth, From Nonlinear Identification to Linear Parameter Varying Models: Benchmark Examples, Workshop on Nonlinear System Identification Benchmarks, 2018. slides, Matlab code

A. Montazeri, M.M. Arefi and M. Kazemi, An Investigation of the Wiener Approach for Nonlinear System Identification Benchmarks, Workshop on Nonlinear System Identification Benchmarks, 2018. slides, Matlab Toolbox

### 2017 Workshop

The second edition of the Workshop on Nonlinear System Identification Benchmarks was held in Brussels, Belgium, April 24-26 2017. This edition was sponsored by the European Research Council (ERC). It featured the talks that are listed below. The complete book of abstracts of the 2017 Workshop on Nonlinear System Identification Benchmarks can be found here.

### Keynote Speakers:

David Barton, University of Bristol

Keynote: Control-based continuation - from models to experiments, slidesLennart Ljung, Linköping University

Keynote: Non-linear system identification: A palette from off-white to pit-black, slidesCarl Edward Rasmussen and Johan Schoukens, University of Cambridge and Vrije Universiteit Brussel

Keynote: Bayesians methods in system identification: equivalences, differences, and misunderstanding, slidesBart Peeters, Siemens PLM Software

Keynote: Structural non-linearities – an industrial view, slides

### Regular Talks:

T. Dossogne, J.P. Noël and G. Kerschen, Nonlinear system identification of an F-16 aircraft using the acceleration surface method, Workshop on Nonlinear System Identification Benchmarks, 2017. slides, toolbox

K. Tiels, Polynomial nonlinear state-space modeling of the F-16 aircraft benchmark, Workshop on Nonlinear System Identification Benchmarks, 2017. slides

P. Dreesen, K. Tiels and M. Ishteva, Decoupling nonlinear models for the F-16 ground vibration test benchmark, Workshop on Nonlinear System Identification Benchmarks, 2017.

G. Hollander, P. Dreesen, M. Ishteva and J. Schoukens, Nonlinear model decoupling using a tensor decomposition initialization, Workshop on Nonlinear System Identification Benchmarks, 2017. slides

T. Münker, T.O. Heinz and O. Nelles, Regularized local FIR model networks for a Bouc-Wen and a Wiener-Hammerstein system, Workshop on Nonlinear System Identification Benchmarks, 2017.

E. Zhang and M. Schoukens, Fast location of process noise for nonlinear system identification, Workshop on Nonlinear System Identification Benchmarks, 2017. slides, Matlab script, Readme in the Matlab script.

B. Tang, M.J. Brennan and G. Gatti, On the interaction of an electro-dynamic shaker and a beam with stiffness nonlinearity, Workshop on Nonlinear System Identification Benchmarks, 2017. slides

G. Giordano and J. Sjöberg, Maximum likelihood identification of Wiener-Hammerstein models in presence of process noise, Workshop on Nonlinear System Identification Benchmarks, 2017. slides

R. Relan, D. Verbeke and K. Tiels, One step ahead prediction of the WH benchmark with process noise using kernel adaptive learning, Workshop on Nonlinear System Identification Benchmarks, 2017. slides

M. Rébillat and M. Schoukens, A methodology to compare two estimation methods for parallel Hammerstein models, Workshop on Nonlinear System Identification Benchmarks, 2017. slides

L. Ljung, Matlab System Identification Toolbox demonstration, Workshop on Nonlinear System Identification Benchmarks, 2017. toolbox, Matlab script

Note that the Matlab script requires Matlab2016b or higher to work, also the F-16 ground vibration test benchmark data should be downloaded.M. Schoukens, Interpolated linear modeling of the F16 benchmark, Workshop on Nonlinear System Identification Benchmarks, 2017. slides, Matlab script

Readme in the Matlab script.P.Z. Csurcsia, G. Birpoutsoukis and J. Schoukens, Transient elimination and memory saving possibilities for multidimensional nonparametric regularization illustrated on the cascaded water tanks benchmark problem, Workshop on Nonlinear System Identification Benchmarks, 2017. slides

S.R. Hassan, System identification of dynamic force transducers, Workshop on Nonlinear System Identification Benchmarks, 2017.

A.F. Esfahani, P. Dreesen, J.P. Noël, K. Tiels, J. Schoukens, Decoupled polynomial nonlinear state space models of a Bouc-Wen hysteretic system, Workshop on Nonlinear System Identification Benchmarks, 2017.

D. Westwick, G. Hollander and J. Schoukens, The decoupled polynomial NARX model: parameter reduction and structural insights for the Bouc-Wen benchmark, Workshop on Nonlinear System Identification Benchmarks, 2017. slides

### 2016 Workshop

The first edition of the Workshop on Nonlinear System Identification Benchmarks was held in Brussels, Belgium, April 25-27 2016. This edition was sponsored by the European Research Council (ERC). It featured the talks that are listed below. The complete book of abstracts of the 2016 Workshop on Nonlinear System Identification Benchmarks can be found here.

### Keynote Speakers:

Gaëtan Kerschen, Université de Liège

Keynote: Identification of Nonlinear Mechanical Systems: State of the Art and Recent Trends, slidesCarl Edward Rasmussen, University of Cambridge

Keynote: Variational Inference in Gaussian Processes for Non-Linear Time Series, slidesThomas Schön, Uppsala Universitet

Keynote: Solving Nonlinear Inference Problems using Sequential Monte Carlo, slidesJohan Schoukens, Vrije Universiteit Brussel

Keynote: Data Driven Discrete Time Modeling of Continuous Time Nonlinear Systems: Problems, Challenges, Success Stories, slidesKeith Worden, The University of Sheffield

Keynote: Is System Identification Just Machine Learning?, slides

### Regular Talks:

K. Tiels, PNLSS 1.0 - A polynomial nonlinear state-space Matlab toolbox, Workshop on Nonlinear System Identification Benchmarks, 2016. slides

A. Svensson, F. Lindsten, T.B. Schön, Particle methods for the Wiener-Hammerstein system, Workshop on Nonlinear System Identification Benchmarks, 2016.

E. Zhang, M. Schoukens, J. Schoukens, Structural modeling of Wiener-Hammerstein system in the presence of the process noise, Workshop on Nonlinear System Identification Benchmarks, 2016. slides

G. Holmes, T. Rogers, E.J. Cross, N. Dervilis, G. Manson, R.J. Barthorpe, K. Worden, Cascaded Tanks Benchmark: Parametric and Nonparametric Identification, Workshop on Nonlinear System Identification Benchmarks, 2016.

G. Giordano, J. Sjöberg, Cascade Tanks Benchmark, Workshop on Nonlinear System Identification Benchmarks, 2016.

J.P. Noël, A.F. Esfahani, G. Kerschen, J. Schoukens, A nonlinear state-space solution to a hysteretic benchmark in system identification, Workshop on Nonlinear System Identification Benchmarks, 2016.

A.F. Esfahani, P. Dreesen, K. Tiels, J.P. Noël, J. Schoukens, Using a polynomial decoupling algorithm for state-space identification of a Bouc-Wen system, Workshop on Nonlinear System Identification Benchmarks, 2016.

R. Gaasbeek, R. Mohan, Control-focused identification of hysteric systems: Selecting model structures? Think about the final use of the model!, Workshop on Nonlinear System Identification Benchmarks, 2016.

A. Bajrić, System identification of a linearized hysteretic system using covariance driven stochastic subspace identification, Workshop on Nonlinear System Identification Benchmarks, 2016.

R. Relan, K. Tiels, A. Marconato, Identifying an Unstructured Flexible Nonlinear Model for the Cascaded Water-tanks Benchmark: Capabilities and Short-comings, Workshop on Nonlinear System Identification Benchmarks, 2016.

P. Mattson, D. Zachariah, P. Stoica, Identification of a PWARX model for the cascade water tanks, Workshop on Nonlinear System Identification Benchmarks, 2016.

G. Birpoutsoukis, P.Z. Csurcsia, Nonparametric Volterra series estimate of the cascaded tank, Workshop on Nonlinear System Identification Benchmarks, 2016.

M. Rébillat, K. Ege, N. Mechbal, J. Antoni, Repeated exponential sine sweeps for the autonomous estimation of nonlinearities and bootstrap assessment of uncertainties, Workshop on Nonlinear System Identification Benchmarks, 2016.

M. Schoukens, Identification of Wiener-Hammerstein systems with process noise using an Errors-in-Variables framework, Workshop on Nonlinear System Identification Benchmarks, 2016.

K. Worden, G. Manson, R.J. Barthorpe, E.J. Cross, N. Dervilis, G. Holmes, T. Rogers, Wiener-Hammerstein Benchmark with process noise: Parametric and Nonparametric Identification, Workshop on Nonlinear System Identification Benchmarks, 2016.

G. Manson, R.J. Barthorpe, E.J. Cross, N. Dervilis, G. Holmes, T. Rogers, K. Worden, Bouc-Wen Benchmark: Parametric and Nonparametric Identification, Workshop on Nonlinear System Identification Benchmarks, 2016.

E. Louarroudi, S. Vanlanduit, R. Pintelon, Identification of non-linear restoring forces through linear time-periodic approximations, Workshop on Nonlinear System Identification Benchmarks, 2016.

M. Schoukens, F.G. Scheiwe, Modeling Nonlinear Systems Using a Volterra Feedback Model, Workshop on Nonlinear System Identification Benchmarks, 2016.

A. Svensson, F. Lindsten, T.B. Schön, First principles and black box modeling of the cascaded water tanks, Workshop on Nonlinear System Identification Benchmarks, 2016.

## Invited Sessions

### IFAC World Congress 2020

Coming soon.

### SYSID 2018

Two invited sessions were organized at the 18th IFAC Symposium on System Identification in Stockholm, Sweden. It featured the following talks:

G. Giordano, J. Sjöberg, Maximum Likelihood Identification of Wiener-Hammerstein System with Process Noise, 18th IFAC Symposium on System Identification (SYSID 2018), 2018, 401-406.

A. Svensson, D. Zachariah, T.B. Schön, How Consistent Is My Model with the Data? Information-Theoretic Model Check, 18th IFAC Symposium on System Identification (SYSID 2018), 2018, 407-412.

J.G. Stoddard, J. Welsh, Regularized Basis Function Estimation of Volterra Kernels for the Cascaded Tanks Benchmark, 18th IFAC Symposium on System Identification (SYSID 2018), 2018, 413-418.

M. Schoukens, R. Toth, From Nonlinear Identification to Linear Parameter Varying Models: Benchmark Examples, 18th IFAC Symposium on System Identification (SYSID 2018), 2018, 419-424.

R. Hostettler, F. Tronarp, S. Särkä Modeling the Drift Function in Stochastic Differential Equations Using Reduced Rank Gaussian Processes, 18th IFAC Symposium on System Identification (SYSID 2018), 2018, 778-783.

M.R.H Abdalmoaty, H. Hjalmarsson, Application of a Linear PEM Estimator to a Stochastic Wiener-Hammerstein Benchmark Problem, 18th IFAC Symposium on System Identification (SYSID 2018), 2018, 784-789.

S. Pan, J. Welsh, An Application of Indirect Inference to the Cascaded Tanks Nonlinear Benchmark, 18th IFAC Symposium on System Identification (SYSID 2018), 2018, 790-795.

D. Westwick, G. Hollander, K. Karami, J. Schoukens, Using Decoupling Methods to Reduce Polynomial NARX Models, 18th IFAC Symposium on System Identification (SYSID 2018), 2018, 796-801.

### IFAC World Congress 2017

An open invited track was organized at the 2017 IFAC World Congres in Toulouse, France. It featured the following talks:

M. Schoukens, J.P. Noël, Three Benchmarks Addressing Open Challenges in Nonlinear System Identification, 20th World Congress The International Federation of Automatic Control, 2017, 448-453. slides

R. Relan, K. Tiels, A. Marconato, J. Schoukens, An Unstructured Flexible Nonlinear Model for the Cascaded Water-Tanks Benchmark, 20th World Congress The International Federation of Automatic Control, 2017, 454-459.

A. Fakhrizadeh Esfahani, P. Dreesen, K. Tiels, J.P. Noël, J. Schoukens, Polynomial State-Space Model Decoupling for the Identification of Hysteretic Systems, 20th World Congress The International Federation of Automatic Control, 2017, 460-465.

M. Brunot, A. Janot, F. Carrillo, Continuous-Time Nonlinear Systems Identification with Output Error Method Based on Derivative-Free Optimisation, 20th World Congress The International Federation of Automatic Control, 2017, 466-471.

J. Belz, T. Münker, T.O. Heinz, G. Kampmann, O. Nelles, Automatic Modeling with Local Model Networks for Benchmark Processes, 20th World Congress The International Federation of Automatic Control, 2017, 472-477.

G. Birpoutsoukis, P.Z. Csurcsia, J. Schoukens, Nonparametric Volterra Series Estimate of the Cascaded Water Tanks Using Multidimensional Regularization, 20th World Congress The International Federation of Automatic Control, 2017, 478-483.