Scope and Objectives
The objective of this workshop is to advance the current knowledge in nonlinear system identification by encouraging the exchange of ideas and the establishment of formal collaborations between the systems and control, mechanical and machine learning communities.
These three communities have developed over the years various and numerous nonlinear modeling approaches driven by the different backgrounds, constraints and end-uses. Moreover, they generally focus on different aspects of the modeling problem as they face different limiting factors in terms of model quality and identification cost. This is why we believe that, by promoting interaction, significant benefit can be mutually gained.
This workshop will be structured around the benchmark systems available through this website. This website hosts both established benchmarks and recently introduced benchmarks featuring state-of-the-art challenges in nonlinear system identification, such as dynamic nonlinearity, process noise, and high order dynamics in combination with a hard nonlinearity.
Solicited contributions should describe solutions or analyses to one or several of the benchmark problems. In particular, comparative overviews of methods would be particularly appreciated. An overview of the results obtained on the featured benchmarks in the past are listed here. Participation in the workshop does not require to submit a contribution, it is of course encouraged.
A hands-on mini-course in nonlinear system identification will take place from Monday 08/04/2019 to Tuesday Noon 09/04/2019, right before the 2019 Benchmark Workshop. This mini-course will cover both parametric and nonparametric identification, linear, block-oriented and nonlinear state-space model structures. A hands-on approach is maintained throughout the course, participants will be able to apply the covered topics to one of the benchmark examples. A detailed program of the mini-course can be found in the workshop book of abstracts here.
The mini-course is open to both workshop participants, and researchers who do not attend the 2019 Benchmark Workshop. Registration for the mini-course is to be completed by the 1st of February, 2019.
The workshop takes place from Wednesday morning 10/04/2019 to Friday noon 12/04/2019. The program overview and book of abstracts can be found here. The list of the confirmed keynote speakers can be found below:
(1) Gianluigi Pillonetto, University of Padova, Italy
Keynote: Regularization networks for system identification
(2) Oliver Nelles, University of Siegen, Germany
Keynote: Challenges in nonlinear system identification
(3) Fredrik Lindsten, Linkoping University, Sweden
Keynote: Learning dynamical systems with particle stochastic approximation EM
(4) Elizabeth Cross, The University of Sheffield, United Kingdom
Keynote: Grey-Box models for structural dynamics
Participant Registration and Deadlines
Early registration for the workshop is to be completed by the 1st of February, 2019. Presenting participants are also requested to submit a 1-page abstract summarizing the main aspects of their contribution by March 15, 2019. An early registration fee of 200 euros is requested for participation in the workshop, the late registration fee is set at 300 euros.
Please email Maarten Schoukens (firstname.lastname@example.org) or Jean-Philippe Noël (email@example.com) to submit your abstract, or ask any other questions.
(1) Late registration deadline: Sunday March 24, 2019, register here.
(2) Abstract submission deadline: Thursday March 21, 2019 - 1-page abstract template available here
(3) Notification of acceptance: Friday March 22, 2019
When and Where
Mini-Course Dates: Monday 08/04/2019 - Tuesday Noon 09/04/2019
Workshop Dates: Wednesday 10/04/2019 - Friday Noon 12/04/2019
Venue: Eindhoven University of Technology, Eindhoven, The Netherlands
The workshop and mini-course venue is on the TU/e campus. Both the lecture room (Collegezaal 2) and the workshop venue (Senaatszaal) are located in the Auditorium building (Campus Map) 10 mins walking from the Eindhoven railway station and 15 mins from the city centre.