Projects per year
Personal profile
Quote
"We need to develop logic engines that can autonomously interact with our applications and to improve their control actions to achieve the desired behavior, by fusing data-driven learning and model-based control engineering."
Research profile
Roland Tóth is Associate Professor in the Control Systems Group in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e). His research interest is in identification and control of physical/chemical systems based on the concept of Linear Parameter-Varying (LPV) models. These models can be imagined as an intermediate step between the well understood framework of Linear Time-Invariant (LTI) systems and the vast universe of nonlinear and time-varying phenomena we experience in practice. One of his main objectives is to bring LPV systems to practical use, through research projects varying from theoretical investigations of hardcore issues of the LPV system theory to practical identification and control of industrial applications.
In addition, Tóth works on the fusion of system identification, control and machine learning methods to develop automated data-driven modeling and controller design approaches for linear/nonlinear systems. The methods are designed to automatically construct dynamical models that capture user-specified aspects of system behavior. In terms of control, policies/algorithms are automatically synthesized by these methods to realize a desired behavior of a system by manipulating its actuators.
Tóth is an Associate Editor of the IEEE Transactions on Control Systems Technology and the International Journal of Robust and Nonlinear Control.
Academic background
Roland Tóth obtained his BSc in Electrical Engineering and MSc degree in Information Technology cum laude from the University of Pannonia (Hungary) in 2004. In 2008, he completed his PhD in Control Engineering at the Delft University of Technology (TU Delft), also cum laude. From 2008 to 2010, Tóth worked as a postdoctoral researcher at TU Delft while also working on a research project for Philips Apptech. In 2010, he joined the University of California (USA) for a postdoc project, before returning to the Netherlands in 2011 to become Assistant Professor at TU Delft. Tóth joined Eindhoven University of Technology as Assistant Professor in 2012 and was promoted to Associate Professor in 2018.
Affiliated with
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DISC (National Graduate School for Systems and Control)
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DATA SCIENCE CENTER
Partners in (semi-)industry :
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ASML
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ALTEN
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Avular
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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DAMOCLES: Data-Augmented Modeling Of Constitutive Laws for Engineering Systems
Tóth, R., Moradi, S., Nawijn, H., Hendrix, W. H. A., Schoukens, M. & Jaensson, N. O.
1/09/21 → 31/08/25
Project: 1st tier research
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Advanced piezo-electric water stage
Van den Hof, P. M. J., Bosman Barros, C., Nawijn, H., van der Hagen, D. & Tóth, R.
1/01/18 → 30/11/25
Project: Research direct
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APROCS: Automated Linear Parameter-Varying Modeling and Control Synthesis for Nonlinear Complex Systems
Tóth, R., Tóth, R., Schoukens, M., Bloemers, T. A. H., Koelewijn, P. J. W., Nawijn, H., Iacob, L. C. & van der Hagen, D.
1/09/17 → 31/03/23
Project: Research direct
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SYSDYNET: Data-Driven Modeling in Dynamic Networks
Van den Hof, P. M. J., Haesaert, S., Kivits, E. M. M., Weiland, S., Lazar, M., Donkers, M. C. F., Tóth, R., Steentjes, T. R. V., Ramaswamy, K., Ludlage, J. H. A., Dreef, H. J., Cheng, X., Nawijn, H., van der Hagen, D., Fonken, S. J. M. & Shi, S.
1/09/16 → 31/08/22
Project: Research direct
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CADUSY: Control And Data-driven modeling Using SYmbolic methods
Van den Hof, P. M. J., Tóth, R., Nawijn, H., Khandelwal, D. & van der Hagen, D.
1/01/16 → 10/01/20
Project: Research direct
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State-space LPV model identification using kernelized machine learning
Rizvi, S. Z., Velni, J. M., Abbasi, F., Tóth, R. & Meskin, N., 1 Feb 2018, In: Automatica. 88, p. 38-47 10 p.Research output: Contribution to journal › Article › Academic › peer-review
35 Citations (Scopus)3 Downloads (Pure) -
Towards efficient identification of linear parameter-varying state-space models
Cox, P. B., 20 Mar 2018, Eindhoven: Technische Universiteit Eindhoven. 341 p.Research output: Thesis › Phd Thesis 1 (Research TU/e / Graduation TU/e)
Open AccessFile1544 Downloads (Pure) -
Direct learning of LPV controllers from data
Formentin, S., Piga, D., Tóth, R. & Savaresi, S. M., 1 Mar 2016, In: Automatica. 65, p. 98-110Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile49 Citations (Scopus)429 Downloads (Pure) -
A review on data-driven linear parameter-varying modeling approaches: A high-purity distillation column case study
Bachnas, A. A., Toth, R., Mesbah, A. & Ludlage, J. H. A., 2014, In: Journal of Process Control. 24, 4, p. 272-285 14 p.Research output: Contribution to journal › Article › Academic › peer-review
85 Citations (Scopus)12 Downloads (Pure) -
Modeling and identification of linear parameter-varying systems
Toth, R., 2010, Berlin: Springer. 325 p. (Lecture notes in control and information sciences; vol. 403)Research output: Book/Report › Book › Academic
207 Citations (Scopus)
Prizes
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Automated Linear Parameter-Varying Modeling and Control Synthesis for Nonlinear Complex Systems
Tóth, Roland (Recipient), 2016
Prize: ERC › Starting › Scientific
Courses
Press/Media
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Advancing control engineering methods to meet current and future challenges
16/02/23
1 item of Media coverage
Press/Media: Expert Comment