Date | Author/Title | | Document Type |
---|
2024 | Liu, Y and Wang, P and Lee, C and Tóth, Roland Attitude Takeover Control for Noncooperative Space Targets Based on Gaussian Processes with Online Model Learning | | Article |
2024 | Antal, Péter and Péni, Tamás and Tóth, Roland Backflipping With Miniature Quadcopters by Gaussian-Process-Based Control and Planning | | Article |
2024 | Koelewijn, P J W and Weiland, S and Tóth, Roland Convex equilibrium-free stability and performance analysis of discrete-time nonlinear systems | | Article |
2024 | Ignéczi, Gergő Ferenc and Horváth, Ernő and Tóth, Roland and Nyilas, K Curve Trajectory Model for Human Preferred Path Planning of Automated Vehicles | | Article |
2024 | Verhoek, C and Berberich, J and Haesaert, S and Allgower, F and Tóth, Roland Data-Driven Dissipativity Analysis of Linear Parameter-Varying Systems | | Article |
2024 | Kon, J and Tóth, Roland and Wijdeven, J V D and Heertjes, M and Oomen, T Guaranteeing Stability in Structured Input-Output Models: With Application to System Identification | | Article |
2024 | Iacob, L C and Tóth, Roland and Schoukens, M Koopman form of nonlinear systems with inputs | | Article |
2024 | Retzler, András and Tóth, Roland and Schoukens, M and Beintema, G I and Weigand, J and Noël, J-P and Kollár, Zsolt and Swevers, J Learning-based augmentation of physics-based models: an industrial robot use case | | Article |
2024 | Beintema, G I and Schoukens, M and Tóth, Roland Meta-state–space learning: An identification approach for stochastic dynamical systems | | Article |
2024 | Bloemers, T and Leemrijse, S and Preda, V and Boquet, F and Oomen, T and Tóth, Roland Vibration Control Under Frequency-Varying Disturbances With Application to Satellites | | Article |
2024 | Wang, R and Tóth, Roland and Koelewijn, P J W and Manchester, I R Virtual control contraction metrics: Convex nonlinear feedback design via behavioral embedding | | Article |
2023 | Khandelwal, D and Schoukens, M and Tóth, Roland Automated multi-objective system identification using grammar-based genetic programming | | Article |
2023 | Antal, Péter and Péni, Tamás and Tóth, Roland Autonóm kvadkopterek modellezése, identifikációja és geometriai szabályozása agilis manőverezéshez | | Article |
2023 | Verhoek, C and Koelewijn, P J W and Haesaert, S and Tóth, Roland Convex incremental dissipativity analysis of nonlinear systems | | Article |
2023 | Beintema, G I and Schoukens, M and Tóth, Roland Deep subspace encoders for nonlinear system identification | | Article |
2023 | Verhoek, C and Abbas, H S and Tóth, Roland Direct data-driven LPV control of nonlinear systems: An experimental result | | Article |
2023 | Polcz, Péter and Péni, Tamás and Tóth, Roland Efficient implementation of Gaussian process–based predictive control by quadratic programming | | Article |
2023 | Iacob, L C and Schoukens, M and Tóth, Roland Finite Dimensional Koopman Form of Polynomial Nonlinear Systems* | | Article |
2023 | Sadeghzadeh, A and Tóth, Roland Improved Embedding of Nonlinear Systems in Linear Parameter-Varying Models with Polinomial Dependence | | Article |
2023 | Ramkannan, R and Beintema, G I and Tóth, Roland and Schoukens, M Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach | | Article |
2023 | Petreczky, M and Tóth, Roland and Mercère, G LPV-ARX representations of LPV state-space models with affine dependence | | Article |
2023 | Petreczky, M and Tóth, Roland and Mercere, G Minimal Realizations of Input-Output Behaviors by LPV State-Space Representations with Affine Dependence | | Article |
2023 | Broens, Y and Butler, H and Tóth, Roland On Improved Commutation for Moving-Magnet Planar Actuators | | Article |
2023 | Moradi, S and Jaensson, N and Tóth, Roland and Schoukens, M Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models | | Article |
2022 | Proimadis, I and Custers, C and Tóth, Roland and Jansen, J W and Butler, H Active deformation control for a magnetically-levitated planar motor mover | | Article |
2022 | Bloemers, T. and Oomen, T. and Tóth, Roland Frequency Response Data-Based LPV Controller Synthesis Applied to a Control Moment Gyroscope | | Article |
2022 | Bloemers, T and Oomen, T and Tóth, Roland Frequency Response Data-driven LPV Controller Synthesis for MIMO Systems | | Article |
2022 | de, Lange M H and Verhoek, C and Preda, V and Tóth, Roland LPV Modeling of the Atmospheric Flight Dynamics of a Generic Parafoil Return Vehicle | | Article |
2022 | Antal, Péter and Péni, Tamás and Tóth, Roland Nonlinear Control Method for Backflipping with Miniature Quadcopters | | Article |
2022 | Iacob, L C and Tóth, Roland and Schoukens, M Optimal Synthesis of LTI Koopman Models for Nonlinear Systems with Inputs | | Article |
2021 | Verhoek, C and Abbas, H S and Tóth, Roland and Haesaert, S Data-Driven Predictive Control for Linear Parameter-Varying Systems | | Article |
2021 | Nechita, S-C and Tóth, Roland and van, Berkel K Data-driven System Identification of Thermal Systems using Machine Learning | | Article |
2021 | Rödönyi, Gábor and Tóth, Roland and Pup, Dániel and Kisari, Ádám and Vigh, Zsombor and Kőrös, Péter and Bokor, József Data-driven linear parameter-varying modelling of the steering dynamics of anautonomous car | | Article |
2021 | Bloemers, T and Tóth, Roland and Oomen, Tom Frequency-Domain Data-Driven Controller Synthesis for Unstable LPV Systems | | Article |
2021 | Rödönyi, Gábor and Beintema, G I and Tóth, Roland and Schoukens, M and Pup, Dániel and Kisari, Ádám and Vigh, Zsombor and Kőrös, Péter and Soumelidis, Alexandros and Bokor, József Identification of the nonlinear steering dynamics of an autonomous vehicle | | Article |
2021 | Koelewijn, P J W and Tóth, Roland Incremental Stability and Performance Analysis of Discrete-Time Nonlinear Systems using the LPV Framework | | Article |
2021 | Abbas, H S and Tóth, Roland and Petreczky, M and Meskin, N and Velni, J M LPV modeling of nonlinear systems: A multi‐path feedback linearization approach | | Article |
2021 | den, Boef P and Cox, P B and Tóth, Roland LPVcore: MATLAB Toolbox for LPV Modelling, Identification and Control | | Article |
2021 | Proimadis, J and Broens, Y and Tóth, Roland and Butler, H Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system | | Article |
2021 | Cox, P B and Tóth, Roland Linear parameter-varying subspace identification: A unified framework | | Article |
2021 | Beintema, G I and Tóth, Roland and Schoukens, M Non-linear State-space Model Identification from Video Data using Deep Encoders | | Article |
2021 | Wang, R and Koelewijn, P J W and Manchester, I R and Tóth, Roland Nonlinear parameter‐varying state‐feedback design for a gyroscope using virtual control contraction metrics | | Article |
2021 | Hanema, J and Tóth, Roland and Lazar, M Stabilizing non‐linear model predictive control using linear parameter‐varying embeddings and tubes | | Article |
2021 | Nechita, S-C and Tóth, Roland and Khandelwal, D and Schoukens, M Toolbox for Discovering Dynamic System Relations via TAG Guided Genetic Programming | | Article |
2020 | Sadeghzadeh, A and Sharif, B and Tóth, Roland Affine linear parameter-varying embedding of non-linear models with improved accuracy and minimal overbounding | | Article |
Date | Author/Title | | Document Type |
---|
2023 | Hoekstra, J H and Cseppentő, Bence and Beintema, G I and Schouken, M and Kollár, Zsolt and Tóth, Roland Computationally efficient predictive control based on ANN state-space models | | Book Section |
2023 | Kon, J and van de Wijdeven, J and Bruijnen, D and Tóth, Roland and Heertjes, M and Oomen, T Direct Learning for Parameter-Varying Feedforward Control: A Neural-Network Approach | | Book Section |
2023 | Verhoek, C and Koelewijn, P J W and Haesaer, S and Tóth, Roland Direct data-driven state-feedback control of general nonlinear systems | | Book Section |
2023 | Vinjarapu, A S H and Broens, Y and Butler, H and Tóth, Roland Exploring the use of deep learning in task-flexible ILC | | Book Section |
2023 | Shakib, M F and Tóth, Roland and Pogromsky, A Y and Pavlov, A and van de Wouw, N Kernel-based learning of stable nonlinear state-space models | | Book Section |
2023 | Verhoek, C and Wang, R and Tóth, Roland Learning Stable and Robust Linear Parameter-Varying State-Space Models | | Book Section |
2023 | Petreczky, M and Tóth, Roland and Mercére, G Minimal realizations of input-output behaviors by LPV state-space representations with affine dependence | | Book Section |
2023 | Broens, Y and Butler, H and Tóth, Roland On Improved Commutation for Moving-Magnet Planar Actuators | | Book Section |
2022 | Verhoek, C and Beintema, G I and Haesaert, S and Schoukens, M and Tóth, Roland Deep-Learning-Based Identification of LPV Models for Nonlinear Systems | | Book Section |
2022 | Bloemers, T A H and Oomen, T A E and Tóth, Roland Frequency Response Data-driven LPV Controller Synthesis for MIMO Systems | | Book Section |
2022 | Broens, Y and Butler, H and Tóth, Roland LPV sequential loop closing for high-precision motion systems * | | Book Section |
2022 | Broens, Y and Butler, H and Tóth, Roland On modal observers for beyond rigid body H_inf control in high-precision mechatronics | | Book Section |
2021 | Iacob, L C and Beintema, G I and Schoukens, M and Tóth, Roland Deep Identification of Nonlinear Systems in Koopman Form | | Book Section |
2021 | Verhoek, C and Tóth, Roland and Haesaert, S and Koch, A Fundamental Lemma for Data-Driven Analysis of Linear Parameter-Varying Systems | | Book Section |
2021 | Koelewijn, P J W and Tóth, Roland and Weiland, S Incremental Dissipativity based Control of Discrete-Time Nonlinear Systems via the LPV Framework | | Book Section |
2021 | Liu, Y and Tóth, Roland Learning Based Model Predictive Control for Quadcopters with Dual Gaussian Process | | Book Section |
2021 | Bosman, Barros C P and Butler, H and van, de Wijdeven J and Tóth, Roland On feedforward control of piezoelectric dual-stage actuator systems | | Book Section |
2021 | Bosman, Barros C P and Butler, H and Tóth, Roland On the Use of the Smith-McMillan Form in Decoupling System Dynamics | | Book Section |