Roland Tóth

Introduction

Roland Tóth is a Senior Research Fellow at the Systems and Control Laboratory in the Institute for Computer Science and Control (SZTAKI) in Budapest, Hungary and he is also an Associate Professor in the Control Systems Group of the Department of Electrical Engineering at the Eindhoven University of Technology (TU/e).

His main research interests are in identification and control of Linear Parameter-Varying (LPV) and nonlinear systems, developing machine learning methods with performance and stability guarantees for modelling and control, model predictive control and behavioural system theory.

On the application side, his research focuses on advancing reliability and performance of precision mechatronics and autonomous robots/vehicles with LPV and learning-based motion control. He is an author of one book and co-author of five edited books and around 150 papers on various aspects modelling and control with LPV methods and machine learning based approaches. He is the main developer of the LPVcore Matlab Toolbox. He is involved in MSc and PhD education both in Hungary and in the Netherlands. So far 5 PhD students have obtained their degrees under his supervision.

He is actively working together with companies such as European Space Agenc (ESA),  ASML, ASMPT, VDL-ETG, Demcon, and his group is part of an IT2 ESCEL consortium. Furthermore,  he has also participated in many industrial research projects and H2020 and FP7 projects. He is a VENI laureate and he has received the Starting Grant of the European Research Council in 2016. He is an Associate Editor of the IEEE Transactions on Control Systems Technology and he was the general chair of the 3rd IFAC Workshop on Linear Parameter-Varying Systems in 2019.

Positions

• Senior Research Fellow, Systems and Control Laboratory, SZTAKI
• Associate Professor in the Control Systems Group of the Department of Electrical Engineering at the Eindhoven University of Technology (TU/e)

Degrees

• BSc in Electrical Engineering cum laude distinction, University of Pannonia, 2004
• MSc in Information Technologies, cum laude distinction, University of Pannonia, 2004
• PhD in Control Engineering, cum laude distinction, Delft University of Technology, 2008
• Dutch University Teaching Qualification (BKO teaching license), 2014

Research Areas

• modelling, system identification and control with the LPV framework
• machine learning based system identification
• learning based control with performance and safety guarantees
• motion control of mechatronic and robotic systems
• navigation and motion control of autonomous vehicles

Memberships and assignments

• Associate Editor, IEEE Transactions on Control Systems Technology (IEEE- TCST)
• European Research Council (ERC) - Starting Grant Award Panel (PE7) member in 2018 and 2020
• Member of the IEEE-CSS technical committee on system identification and adaptive control.
• Member of the IFAC technical committees: TC 1.1 – Modelling, Identification and Signal Processing and TC 2.2 – Linear Control Systems
• Member of the European Research Network of System Identification (ERNSI)
• Senior Member of the Institute of Electrical and Electronics Engineers (IEEE)

Educational Activity

Eindhoven University of Technology

• Machine Learning for Modelling and Control [5SC28], MSc level, lecturer
• Responsible Lecturer – Robust Control [5LMC0], MSc level, responsible lecturer
• Instructor – Integration Project: Lab work [5SC26], MSc level, instructor

Selected projects

• 2021-24  "Fault-Tolerant Active Vibration Isolation Platform for Adaptable Payloads " [co-PI], ESA OSIP programe.
• 2021-22 "Artificial intelligence techniques for GNC design, implementation and verification (AI4GNC)" [PI and WP leader at TU/e], in co-op with Sener Aerospecial and University of Stuttgart, ESA Tender.
• 2020-23 “IC Technology for the 2nm Node” [co-PI, WP leader at TU/e], ECSEL Research and Innovation Actions of the European Commission
• 2017-22 “Automated Linear Parameter-Varying Modeling and Control Synthesis for Nonlinear Complex Systems (APROCS)” [PI] 5 years funding by the European Research Council
• 2016-20 “Control and data-driven modeling using symbolic methods (CADUSY)” [co-PI] 4 years of funding with industrial collaboration: ASML, National Instruments, Evolved Analytics, FMTC, in co-op with TUDelft, (Embedded Systems call, STW Netherlands)
• 2015-19 “Nanometer-accurate planar actuation system (NAPAS)” [co-PI], 4 years of funding with industrial collaboration: ASML, Philips, Prodrive, Tecnotion, SKF, TNO (HTSM call, STW Netherlands)
• 2014-18 “Next Generation Mechatronics” [co-PI], ASML-TU/e Impulse program

Publication databases

• Repository of Hungarian Scientific Works
• Personal publication list
• Google Scholar
• Scopus
• Pure

Selected publications:

• Linear Parameter-Varying Subspace Identification: A Unified Framework.
  Authors: Cox, P. B.; Tóth, R.
  Publication date: 2020
• Sparse RKHS estimation via globally convex optimization and its application in LPV-IO identification
  Authors: Laurain, V.; Tóth, R.; Piga, D.; Darwish, M.A.H.
  Publication date: 2020
• A Tree Adjoining Grammar representation for models of stochastic dynamical systems
  Authors: Khandelwal, D.;  Schoukens M.; Tóth, R.
  Publication date: 2020
• Linear Parameter-Varying Control of Nonlinear Systems based on Incremental Stability
  Authors: Koelewijn, P.J.W.; Tóth, R.; Nijmeijer, H.
  Publication date: 2019
• Learning based Approximate Model Predictive Control for constrained qLPV systems
  Authors: Gángó, D.; Péni, T.;  Tóth, R.
  Publication date: 2019
• Prediction-Error Identification of LPV Systems: A Nonparametric Gaussian Regression Approach
  Authors: Darwish , M. A. H.; Cox, P. B.; Proimadis, I.; Pillonetto G.; Tóth, R.
  Publication date: 2018
• Modeling and identification of linear parameter-varying systems.
  Authors: Tóth, R.
  Publication date: 2010