Chris Verhoek -- Research

On this page you can find information and news about my adventures in terms of research. You can find the list of my publications here.

24-07-2024

Our paper on biquadratic Lyapunov forms in data-driven LPV control has been accepted for presentation at the CDC in 2024! You can check the paper here.

23-06-2024

I'm happy to share that our paper on data-driven dissipativity analysis of LPV systems has been accepted as a full paper in IEEE Transactions on Automatic Control! You can check out the early access version here.

14-11-2023

New paper online! We finished the LPV extension on data-driven predictive control for both the state-feedback and output-feedback case. Of course we a guideline how to use this for nonlinear systems and/or noisy data! Check out the paper here.

24-09-2023

Today my 6 week-long visit at Florian Dörfler's group starts at ETH Zürich. I will give two talks there; a talk summarizing my research from the past year(s), and a tutorial on the LPV framework. I will also visit EPFL for a few days in the end of October.
EDIT (06-11-2023): This was an amazing experience. I've been welcomed with open arms on both an academic and social level. IfA can be proud of being such a nice, vibrant group!

10-07-2023

I presented my paper "Direct data-driven LPV control of nonlinear systems: An experimental result" at the IFAC conference today. Next to that, it was also my birthday! What a nice way to celebrate your birthday in Japan! I also found out that for the CDC decision notifications, the two papers where I'm the main author have been accepted for presentation!

04-04-2023

Now that the CDC deadline has passed, I'm glad to tell you that we have submitted four contributions!
One joint L-CSS submission (which we hope is a landmark paper) that combines the universal shifted stability and performance ideas with data-driven LPV control. You can read that paper here.
Three regular submissions, which is mainly joint work with wonderful people. Two are on data-driven analysis and (STL) control of LTI systems, while the other one is on the machine learning research line. The latter develops a stable and robust parametrization for learning LPV-ANN models.

01-02-2023

Our Automatica paper Automatica paper "Convex Incremental Dissipativity Analysis of Nonlinear Systems" is now available online and can be read here: doi.org/10.1016/j.automatica.2023.110859.

01-12-2022

What is better to end the year with some nice announcements.
First of all, our Automatica paper "Convex Incremental Dissipativity Analysis of Nonlinear Systems" has been accepted for publication! The extended version of the final submitted version can be found here.
Secondly, we finished two papers on the data-driven LPV control research line; one journal paper (submitted to IEEE-TAC) titled "Direct Data-Driven State-Feedback Control of LPV Systems" and a conference paper (submitted to IFAC2023) titled "Direct data-driven LPV control of nonlinear systems: An experimental result". Both papers discuss the direct data-driven synthesis of LPV state-feedback controllers, where the journal paper discusses all the theory, while the conference paper applies the theory in an experimental setting. In the end, we saw that one will only need 7 time-steps of measurement data for the design of an LPV state-feedback controller for an unbalanced disc system. See also a video of the experiments here and here.
And finally, the LPVS paper has been published in the LPVS proceedings. You can find it here.

17-07-2022

Good news! The paper Deep-Learning-Based Identification of LPV Models for Nonlinear Systems is accepted for presentation at, and publication in the proceedings of, the 61st IEEE Conference on Decision and Control in Cancun, Mexico. And the paper LPV Modeling of the Atmospheric Flight Dynamics of a Generic Parafoil Return Vehicle that we submitted to the 5th IFAC Workshop on Linear Parameter Varying Systems is also accepted for presentation and publication!

19-05-2022

We have two new pre-prints online: a paper on Deep-Learning-Based Identification of LPV Models for Nonlinear Systems and a paper on the LPV Modeling of the Atmospheric Flight Dynamics of a Generic Parafoil Return Vehicle. Enjoy the read!

23-02-2022

Our paper "Fundamental Lemma for Data-Driven Analysis of Linear Parameter-Varying Systems" has been published in the proceedings of the 60th IEEE Conference on Decision and Control (CDC). You can find it here.

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For some occasions, I write a short blog post. All these occasions are listed here:

List of presentation slides

This post is simply a list of the presentations I gave during conferences or visits, including links to the slides.

List of released code and software

This post is simply a list of links to gitlab repositories that contain the code that I released for an article.

Predictions with the Fundamental Lemma for LPV Systems

In this post, we want to add some extra information regarding the final prediction example of our 2021 CDC paper in terms of simulation data.

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Journal papers

1. C. Verhoek, J. Berberich, S. Haesaert, R. Tóth, and H. S. Abbas. "A Linear Parameter-Varying Approach to Data Predictive Control." Submitted to IEEE Transactions on Automatic Control, 2023. (pdf, bibtex)
2. C. Verhoek, J. Berberich, S. Haesaert, F. Allgöwer and R. Tóth. "Data-driven Dissipativity Analysis of Linear Parameter-Varying Systems." IEEE Transactions on Automatic Control, 2024. (pdf, bibtex)
3. C. Verhoek, R. Tóth and H.S. Abbas. "Direct Data-Driven State-Feedback Control of Linear Parameter-Varying Systems." Submitted to International Journal of Robust and Nonlinear Control, 2024. (pdf, bibtex)
4. C. Verhoek, P.J.W. Koelewijn, S. Haesaert, and R. Tóth. "Convex Incremental Dissipativity Analysis of Nonlinear Systems." Automatica, vol. 150, p. 110859, 2023. (pdf, bibtex)

Conference papers

1. C. Verhoek, J. Eising, F. Dörfler, and R. Tóth. "Decoupling parameter variation from noise: Biquadratic Lyapunov forms in data-driven LPV control." Accepted for the 63rd IEEE Conference on Decision and Control (CDC), 2024. (pdf, bibtex)
2. J.H. Hoekstra, C. Verhoek, R. Tóth, and M. Schoukens. "Learning-based model augmentation with LFRs." Submitted to the 63rd IEEE Conference on Decision and Control (CDC), 2024. (pdf, bibtex)
3. L.M. Spin, C. Verhoek, W.P.M.H. Heemels, N. van de Wouw, and R. Tóth. "Unified Behavioral Data-Driven Performance Analysis: A Generalized Plant Approach." Accepted for the 2024 European Control Conference (ECC), 2024. (pdf, bibtex)
4. B.C. van Huijgevoort, C. Verhoek, R. Tóth and S. Haesaert. "Direct data-driven signal temporal logic control of linear systems." Accepted for the 8th IFAC Conference on Analysis and Design of Hybrid Systems (ADHS), 2024. (pdf, bibtex)
5. C. Verhoek, P.J.W. Koelewijn, S. Haesaert, and R. Tóth. "Direct data-driven state-feedback control of general nonlinear systems." In Proc. of the 62nd IEEE Conference on Decision and Control (CDC), 2023, pp. 3688-3693. (pdf, bibtex)
6. C. Verhoek, R. Wang, and R. Tóth. "Learning Stable and Robust Linear Parameter-Varying State-Space Models." In Proc. of the 62nd IEEE Conference on Decision and Control (CDC), 2023, pp. 1348-1353. (pdf, bibtex)
7. L. Hewing, D. Gramlich, C. Verhoek, et al. "Enhancing the Guidance, Navigation, and Control of Autonomous Parafoils using Machine Learning Methods." In Proc. of the 12th International Conference on Guidance, Navigation & Control Systems, 2023. (pdf, bibtex)
8. C. Verhoek, H.S. Abbas and R. Tóth. "Direct data-driven LPV control of nonlinear systems: An experimental result." In Proc. of the 22nd IFAC World Congress 2023 (IFAC2023), 2023, pp. 2263-2268. (pdf, bibtex)
9. C. Verhoek, G.I. Beintema, S. Haesaert, M. Schoukens and R. Tóth. "Deep-Learning-Based Identification of LPV Models for Nonlinear Systems." In Proc. of the 61st IEEE Conference on Decision and Control (CDC), 2022, pp. 3274-3280. (pdf, bibtex)
10. M.H. de Lange, C. Verhoek, V. Preda and R. Tóth. "LPV Modeling of the Atmospheric Flight Dynamics of a Generic Parafoil Return Vehicle." In Proc. of the 5th IFAC Workshop on Linear Parameter Varying Systems (LPVS), 2022. (pdf, bibtex)
11. C. Verhoek, R. Tóth, S. Haesaert, and A. Koch. "Fundamental Lemma for Data-Driven Analysis of Linear Parameter-Varying Systems." In Proc. of the 60th IEEE Conference on Decision and Control (CDC), 2021, pp. 5040-5046. (pdf, bibtex)
12. C. Verhoek, H.S. Abbas, R. Tóth, and S. Haesaert. "Data-Driven Predictive Control for Linear Parameter-Varying Systems." In Proc. of the 4th IFAC Workshop on Linear Parameter-Varying Systems (LPVS), 2021. (pdf, bibtex)

Abstracts

1. C. Verhoek, S. Haesaert, and R. Tóth. "An experimental result on direct data-driven control of nonlinear systems using the LPV framework." In Proc. of the 2023 Benelux Workshop on Systems and Control, p. 214, 2023. (pdf, bibtex)
2. C. Verhoek, G. I. Beintema, S. Haesaert, M. Schoukens and R. Tóth. "Learning-Based Model-Augmentation of Nonlinear Approximative Models using the Sub-Space Encoder." In Proc. of the 2022 Benelux Workshop on Systems and Control, p. 52, 2022. (pdf, bibtex)
3. C. Verhoek, R. Tóth, and S. Haesaert. "Data-Driven Predictive Control of Linear Parameter-Varying Systems." In Proc. of the 2021 Benelux Workshop on Systems and Control, p. 55, 2021. (pdf, bibtex)
4. C. Verhoek, P.J.W. Koelewijn, and R. Tóth. "Incremental Dissipativity Analysis of Nonlinear Systems using the Linear Parameter-Varying Framework." In Proc. of the 39th Benelux Meeting on Systems and Control, p. 75, 2020. (pdf, bibtex)

Theses

1. C. Verhoek, "Incremental Dissipativity Based Control of Nonlinear Systems," MSc Thesis, Eindhoven University of Technology, 2020. (pdf, bibtex)

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