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

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:

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

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

  11. 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.

  12. 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

  13. 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:

  1. Gianluigi Pillonetto, University of Padova, Italy
    Keynote:
    Regularization networks for system identification, slides

  2. Oliver Nelles, University of Siegen, Germany
    Keynote:
    Challenges in nonlinear system identification, slides

  3. Fredrik Lindsten, Linkoping University, Sweden
    Keynote:
    Learning dynamical systems with particle stochastic approximation EM, slides

  4. Elizabeth Cross, The University of Sheffield, United Kingdom
    Keynote:
    Grey-Box models for structural dynamics, slides

Regular Talks:

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

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

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

  4. 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

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

  6. 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

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

  8. 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.

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

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

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

  12. 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

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

  14. 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.

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

  16. 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.

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

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

  19. 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:

  1. Eleni Chatzi, ETH Zürich, Switzerland
    Keynote:
    Data-Driven Assessment of Engineered Systems: Beyond LTI, slides

  2. Alfred Schouten TU Delft, The Netherlands
    Keynote:
    Nonlinear cortical responses in EEG evoked by continuous wrist manipulations, slides

  3. Johan Suykens, KU Leuven, Belgium
    Keynote:
    Function estimation, model representations and nonlinear system identification, slides

  4. Peter Young, University of Lancaster, UK
    Keynote:
    State-Dependent Parameter (SDP) Nonlinear Models and a Hydrological Identification Benchmark, slides, demo and background material

  5. Jorge Goncalves, University of Luxembourg, Luxembourg
    Keynote:
    Challenges in system identification of biochemical systems, slides

Regular Talks:

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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.

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

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

  10. 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

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

  12. 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.

  13. 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.

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

  15. 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

  16. 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:

  1. David Barton, University of Bristol
    Keynote:
    Control-based continuation - from models to experiments, slides

  2. Lennart Ljung, Linköping University
    Keynote:
    Non-linear system identification: A palette from off-white to pit-black, slides

  3. Carl Edward Rasmussen and Johan Schoukens, University of Cambridge and Vrije Universiteit Brussel
    Keynote:
    Bayesians methods in system identification: equivalences, differences, and misunderstanding, slides

  4. Bart Peeters, Siemens PLM Software
    Keynote:
    Structural non-linearities – an industrial view, slides

Regular Talks:

  1. 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

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

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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

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

  11. 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.

  12. M. Schoukens, Interpolated linear modeling of the F16 benchmark, Workshop on Nonlinear System Identification Benchmarks, 2017. slides, Matlab script
    Readme in the Matlab script.

  13. 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

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

  15. 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.

  16. 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:

  1. Gaëtan Kerschen, Université de Liège
    Keynote:
    Identification of Nonlinear Mechanical Systems: State of the Art and Recent Trends, slides

  2. Carl Edward Rasmussen, University of Cambridge
    Keynote:
    Variational Inference in Gaussian Processes for Non-Linear Time Series, slides

  3. Thomas Schön, Uppsala Universitet
    Keynote:
    Solving Nonlinear Inference Problems using Sequential Monte Carlo, slides

  4. Johan Schoukens, Vrije Universiteit Brussel
    Keynote:
    Data Driven Discrete Time Modeling of Continuous Time Nonlinear Systems: Problems, Challenges, Success Stories, slides

  5. Keith Worden, The University of Sheffield
    Keynote:
    Is System Identification Just Machine Learning?, slides

Regular Talks:

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

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

  3. 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

  4. 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.

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

  6. 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.

  7. 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.

  8. 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.

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

  10. 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.

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

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

  13. 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.

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

  15. 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.

  16. 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.

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

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

  19. 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:

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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:

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.