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2020 – today
- 2024
[j42]Lucian-Cristian Iacob, Roland Tóth, Maarten Schoukens:
Koopman form of nonlinear systems with inputs. Autom. 162: 111525 (2024)- [j41]Gerben Izaak Beintema
, Maarten Schoukens, Roland Tóth:
Meta-state-space learning: An identification approach for stochastic dynamical systems. Autom. 167: 111787 (2024) - [j40]Johan Kon, Roland Tóth, Jeroen van de Wijdeven, Marcel Heertjes, Tom Oomen:
Guaranteeing Stability in Structured Input-Output Models: With Application to System Identification. IEEE Control. Syst. Lett. 8: 1565-1570 (2024) - [j39]Yuhan Liu, Pengyu Wang, Chang-Hun Lee, Roland Tóth:
Attitude Takeover Control for Noncooperative Space Targets Based on Gaussian Processes With Online Model Learning. IEEE Trans. Aerosp. Electron. Syst. 60(3): 3050-3066 (2024) - [j38]Péter Antal, Tamás Péni, Roland Tóth:
Backflipping With Miniature Quadcopters by Gaussian-Process-Based Control and Planning. IEEE Trans. Control. Syst. Technol. 32(1): 3-14 (2024) - [j37]Tom Bloemers, Sjoerd Leemrijse, Valentin Preda, Fabrice Boquet, Tom Oomen, Roland Tóth:
Vibration Control Under Frequency-Varying Disturbances With Application to Satellites. IEEE Trans. Control. Syst. Technol. 32(6): 1983-1994 (2024) - [c78]Péter Antal, Tamás Péni, Roland Tóth:
Computationally Efficient Sampling-Based Algorithm for Stability Analysis of Nonlinear Systems. ECC 2024: 180-185 - [c77]Kristóf Floch, Tamás Péni, Roland Tóth:
Gaussian-Process-Based Adaptive Trajectory Tracking Control for Autonomous Ground Vehicles. ECC 2024: 464-471 - [c76]L. M. Spin, Chris Verhoek, W. P. M. H. Heemels, Nathan van de Wouw, Roland Tóth:
Unified Behavioral Data-Driven Performance Analysis A Generalized Plant Approach. ECC 2024: 894-899 - [c75]Johan Kon, Jeroen van de Wijdeven, Dennis Bruijnen, Roland Tóth, Marcel Heertjes, Tom Oomen:
Unconstrained Parameterization of Stable LPV Input-Output Models: with Application to System Identification. ECC 2024: 2143-2148 - [i90]Jonas Weigand, Gerben Izaak Beintema, Jonas Ulmen, Daniel Görges, Roland Tóth, Maarten Schoukens, Martin Ruskowski:
State Derivative Normalization for Continuous-Time Deep Neural Networks. CoRR abs/2401.02902 (2024) - [i89]Johan Kon, Jeroen van de Wijdeven, Dennis Bruijnen, Roland Tóth, Marcel Heertjes, Tom Oomen:
Unconstrained Parameterization of Stable LPV Input-Output Models: with Application to System Identification. CoRR abs/2401.10052 (2024) - [i88]Patrick J. W. Koelewijn, Siep Weiland, Roland Tóth:
Convex Equilibrium-Free Stability and Performance Analysis of Discrete-Time Nonlinear Systems. CoRR abs/2402.09870 (2024) - [i87]Yorick Broens, Hans Butler, Roland Tóth:
Frequency Domain Auto-tuning of Structured LPV Controllers for High-Precision Motion Control. CoRR abs/2403.05878 (2024) - [i86]Chris Verhoek, Jaap Eising, Florian Dörfler, Roland Tóth:
Decoupling parameter variation from noise: Biquadratic Lyapunov forms in data-driven LPV control. CoRR abs/2403.16565 (2024) - [i85]E. Javier Olucha, Bogoljub Terzin, Amritam Das, Roland Tóth:
On the reduction of Linear Parameter-Varying State-Space models. CoRR abs/2404.01871 (2024) - [i84]Jan H. Hoekstra, Chris Verhoek, Roland Tóth, Maarten Schoukens:
Learning-based model augmentation with LFRs. CoRR abs/2404.01901 (2024) - [i83]Petar Bevanda, Bas Driessen, Lucian-Cristian Iacob, Roland Tóth, Stefan Sosnowski, Sandra Hirche:
Nonparametric Control-Koopman Operator Learning: Flexible and Scalable Models for Prediction and Control. CoRR abs/2405.07312 (2024) - [i82]Yuhan Liu, Roland Tóth, Maarten Schoukens:
Physics-Guided State-Space Model Augmentation Using Weighted Regularized Neural Networks. CoRR abs/2405.10429 (2024) - [i81]Max D. Champneys, Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens, Timothy J. Rogers:
Baseline Results for Selected Nonlinear System Identification Benchmarks. CoRR abs/2405.10779 (2024) - [i80]Péter Antal, Tamás Péni, Roland Tóth:
Computationally Efficient Sampling-Based Algorithm for Stability Analysis of Nonlinear Systems. CoRR abs/2405.13750 (2024) - [i79]Máté Kiss, Roland Tóth, Maarten Schoukens:
Space-Filling Input Design for Nonlinear State-Space Identification. CoRR abs/2405.18207 (2024) - [i78]Chris Verhoek, Roland Tóth:
Kernel-based multi-step predictors for data-driven analysis and control of nonlinear systems through the velocity form. CoRR abs/2408.00688 (2024) - [i77]Péter Antal, Tamás Péni, Roland Tóth:
Hook-Based Aerial Payload Grasping from a Moving Platform. CoRR abs/2409.11788 (2024) - 2023
- [j36]Chris Verhoek, Patrick J. W. Koelewijn, Sofie Haesaert, Roland Tóth:
Convex incremental dissipativity analysis of nonlinear systems. Autom. 150: 110859 (2023) - [j35]Dhruv Khandelwal, Maarten Schoukens, Roland Tóth:
Automated multi-objective system identification using grammar-based genetic programming. Autom. 154: 111017 (2023) - [j34]Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Deep subspace encoders for nonlinear system identification. Autom. 156: 111210 (2023) - [j33]Yorick Broens, Hans Butler, Roland Tóth:
On Improved Commutation for Moving-Magnet Planar Actuators. IEEE Control. Syst. Lett. 7: 2593-2598 (2023) - [j32]Mihály Petreczky, Roland Tóth, Guillaume Mercère:
Minimal Realizations of Input-Output Behaviors by LPV State-Space Representations With Affine Dependence. IEEE Control. Syst. Lett. 7: 2952-2957 (2023) - [j31]Mihály Petreczky, Roland Tóth, Guillaume Mercère:
LPV-ARX representations of LPV state-space models with affine dependence. Syst. Control. Lett. 173: 105459 (2023) - [j30]Arash Sadeghzadeh, Roland Tóth:
Improved Embedding of Nonlinear Systems in Linear Parameter-Varying Models With Polynomial Dependence. IEEE Trans. Control. Syst. Technol. 31(1): 70-82 (2023) - [c74]Anantha Sai Hariharan Vinjarapu, Yorick Broens, Hans Butler, Roland Tóth:
Exploring the use of deep learning in task-flexible ILC*. ACC 2023: 2751-2756 - [c73]Chris Verhoek, Ruigang Wang, Roland Tóth:
Learning Stable and Robust Linear Parameter-Varying State-Space Models. CDC 2023: 1348-1353 - [c72]Mohammad Fahim Shakib, Roland Tóth, Alexander Yu. Pogromsky, A. Pavlov, Nathan van de Wouw:
Kernel-Based Learning of Stable Nonlinear State-Space Models. CDC 2023: 2897-2902 - [c71]Chris Verhoek, Patrick J. W. Koelewijn, Sofie Haesaert, Roland Tóth:
Direct Data-Driven State-Feedback Control of General Nonlinear Systems. CDC 2023: 3688-3693 - [c70]Johan Kon, Jeroen van de Wijdeven, Dennis Bruijnen, Roland Tóth, Marcel Heertjes, Tom Oomen:
Direct Learning for Parameter-Varying Feedforward Control: A Neural-Network Approach. CDC 2023: 3720-3725 - [c69]Jan H. Hoekstra, Bence Cseppento, Gerben Izaak Beintema, Maarten Schoukens, Zsolt Kollár, Roland Tóth:
Computationally Efficient Predictive Control Based on ANN State-Space Models. CDC 2023: 6336-6341 - [c68]Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Continuous-time identification of dynamic state-space models by deep subspace encoding. ICLR 2023 - [i76]Lucian-Cristian Iacob, Maarten Schoukens, Roland Tóth:
Finite Dimensional Koopman Form of Polynomial Nonlinear Systems. CoRR abs/2301.06557 (2023) - [i75]Chris Verhoek, Julian Berberich, Sofie Haesaert, Frank Allgöwer, Roland Tóth:
Data-driven Dissipativity Analysis of Linear Parameter-Varying Systems. CoRR abs/2303.10031 (2023) - [i74]Chris Verhoek, Patrick J. W. Koelewijn, Sofie Haesaert, Roland Tóth:
Direct data-driven state-feedback control of general nonlinear systems. CoRR abs/2303.10648 (2023) - [i73]Yorick Broens, Hans Butler, Roland Tóth:
On improved commutation for moving-magnet planar actuators. CoRR abs/2303.14392 (2023) - [i72]Anantha Sai Hariharan Vinjarapu, Yorick Broens, Hans Butler, Roland Tóth:
Exploring the use of deep learning in task-flexible ILC. CoRR abs/2303.14402 (2023) - [i71]Jan H. Hoekstra, Bence Cseppento, Gerben Izaak Beintema, Maarten Schoukens, Zsolt Kollár, Roland Tóth:
Computationally efficient predictive control based on ANN state-space models. CoRR abs/2303.17305 (2023) - [i70]Chris Verhoek, Ruigang Wang, Roland Tóth:
Learning Stable and Robust Linear Parameter-Varying State-Space Models. CoRR abs/2304.01828 (2023) - [i69]L. M. Spin, Chris Verhoek, W. P. Maurice H. Heemels, Nathan van de Wouw, Roland Tóth:
Unified Behavioral Data-Driven Performance Analysis: A Generalized Plant Approach. CoRR abs/2304.01859 (2023) - [i68]Rishi Ramkannan, Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens:
Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach. CoRR abs/2304.02119 (2023) - [i67]Birgit van Huijgevoort, Chris Verhoek, Roland Tóth, Sofie Haesaert:
Direct data-driven signal temporal logic control of linear systems. CoRR abs/2304.02297 (2023) - [i66]Péter Antal, Tamás Péni, Roland Tóth:
Payload Grasping and Transportation by a Quadrotor with a Hook-Based Manipulator. CoRR abs/2304.02444 (2023) - [i65]Sarvin Moradi, Nick Jaensson, Roland Tóth, Maarten Schoukens:
Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models. CoRR abs/2305.01338 (2023) - [i64]Péter Antal, Tamás Péni, Roland Tóth:
Modelling, identification and geometric control of autonomous quadcopters for agile maneuvering. CoRR abs/2306.09651 (2023) - [i63]Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Meta-State-Space Learning: An Identification Approach for Stochastic Dynamical Systems. CoRR abs/2307.06675 (2023) - [i62]Patrick J. W. Koelewijn, Siep Weiland, Roland Tóth:
Equilibrium-Independent Control of Continuous-Time Nonlinear Systems via the LPV Framework - Extended Version. CoRR abs/2308.08335 (2023) - [i61]Johan Kon, Jeroen van de Wijdeven, Dennis Bruijnen, Roland Tóth, Marcel Heertjes, Tom Oomen:
Direct Learning for Parameter-Varying Feedforward Control: A Neural-Network Approach. CoRR abs/2309.12722 (2023) - [i60]Gergo Ignéczi, Erno Horváth, Roland Tóth, Krisztian Nyilas:
Curve Trajectory Model for Human Preferred Path Planning of Automated Vehicles. CoRR abs/2310.02696 (2023) - [i59]Yuhan Liu, Pengyu Wang, Chang-Hun Lee, Roland Tóth:
Attitude Takeover Control for Noncooperative Space Targets Based on Gaussian Processes with Online Model Learning. CoRR abs/2310.15883 (2023) - [i58]Chris Verhoek, Julian Berberich, Sofie Haesaert, Roland Tóth, Hossam S. Abbas:
A Linear Parameter-Varying Approach to Data Predictive Control. CoRR abs/2311.07140 (2023) - [i57]Patrick J. W. Koelewijn, Rajiv Sing, Peter J. Seiler, Roland Tóth:
Learning Reduced-Order Linear Parameter-Varying Models of Nonlinear Systems. CoRR abs/2312.06217 (2023) - 2022
- [j29]Tom Bloemers, Tom Oomen, Roland Tóth:
Frequency Response Data-Driven LPV Controller Synthesis for MIMO Systems. IEEE Control. Syst. Lett. 6: 2264-2269 (2022) - [j28]Tom Bloemers, Tom Oomen, Roland Tóth:
Frequency Response Data-Based LPV Controller Synthesis Applied to a Control Moment Gyroscope. IEEE Trans. Control. Syst. Technol. 30(6): 2734-2742 (2022) - [c67]Yorick Broens, Hans Butler, Roland Tóth:
LPV sequential loop closing for high-precision motion systems*. ACC 2022: 3178-3183 - [c66]Yorick Broens, Hans Butler, Roland Tóth:
On modal observers for beyond rigid body H∞ control in high-precision mechatronics*. CDC 2022: 1722-1727 - [c65]Chris Verhoek, Gerben Izaak Beintema, Sofie Haesaert, Maarten Schoukens, Roland Tóth:
Deep-Learning-Based Identification of LPV Models for Nonlinear Systems. CDC 2022: 3274-3280 - [i56]Yorick Broens, Hans Butler, Roland Tóth:
On discretization of continuous-time LPV control solutions. CoRR abs/2202.03177 (2022) - [i55]Yorick Broens, Hans Butler, Roland Tóth:
LPV sequential loop closing for high-precision motion systems. CoRR abs/2203.08287 (2022) - [i54]Chris Verhoek, Gerben Izaak Beintema, Sofie Haesaert, Maarten Schoukens, Roland Tóth:
Deep-Learning-Based Identification of LPV Models for Nonlinear Systems. CoRR abs/2204.04060 (2022) - [i53]Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Deep subspace encoders for continuous-time state-space identification. CoRR abs/2204.09405 (2022) - [i52]Matthis H. de Lange, Chris Verhoek, Valentin Preda, Roland Tóth:
LPV Modeling of the Atmospheric Flight Dynamics of a Generic Parafoil Return Vehicle. CoRR abs/2205.09555 (2022) - [i51]Lucian-Cristian Iacob, Roland Tóth, Maarten Schoukens:
Optimal Synthesis of LTI Koopman Models for Nonlinear Systems with Inputs. CoRR abs/2206.07534 (2022) - [i50]Lucian-Cristian Iacob, Roland Tóth, Maarten Schoukens:
Koopman Form of Nonlinear Systems with Inputs. CoRR abs/2207.12132 (2022) - [i49]Yorick Broens, Hans Butler, Roland Tóth:
On modal observers for beyond rigid body H∞ control in high-precision mechatronics. CoRR abs/2209.06554 (2022) - [i48]Peter Antal, Tamás Péni, Roland Tóth:
Backflipping with Miniature Quadcopters by Gaussian Process Based Control and Planning. CoRR abs/2209.14652 (2022) - [i47]Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Deep Subspace Encoders for Nonlinear System Identification. CoRR abs/2210.14816 (2022) - [i46]Yuhan Liu, Pengyu Wang, Roland Tóth:
Learning For Predictive Control: A Dual Gaussian Process Approach. CoRR abs/2211.03699 (2022) - [i45]Chris Verhoek, Roland Tóth, Hossam S. Abbas:
Direct Data-Driven State-Feedback Control of Linear Parameter-Varying Systems. CoRR abs/2211.17182 (2022) - [i44]Chris Verhoek, Hossam S. Abbas, Roland Tóth:
Direct data-driven LPV control of nonlinear systems: An experimental result. CoRR abs/2211.17191 (2022) - 2021
- [j27]Pepijn Bastiaan Cox, Roland Tóth:
Linear parameter-varying subspace identification: A unified framework. Autom. 123: 109296 (2021) - [c64]Clarisse Pétua Bosman Barros, Hans Butler, Roland Tóth:
On the Use of the Smith-McMillan Form in Decoupling System Dynamics. ACC 2021: 2069-2074 - [c63]Yuhan Liu, Roland Tóth:
Learning Based Model Predictive Control for Quadcopters with Dual Gaussian Process. CDC 2021: 1515-1521 - [c62]Lucian-Cristian Iacob, Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Deep Identification of Nonlinear Systems in Koopman Form. CDC 2021: 2288-2293 - [c61]Patrick J. W. Koelewijn, Roland Tóth, Siep Weiland:
Incremental Dissipativity based Control of Discrete-Time Nonlinear Systems via the LPV Framework. CDC 2021: 3281-3286 - [c60]Chris Verhoek, Roland Tóth, Sofie Haesaert, Anne Koch:
Fundamental Lemma for Data-Driven Analysis of Linear Parameter-Varying Systems. CDC 2021: 5040-5046 - [c59]Clarisse Pétua Bosman Barros, Hans Butler, Jeroen van de Wijdeven, Roland Tóth:
On feedforward control of piezoelectric dual-stage actuator systems. CDC 2021: 5588-5594 - [c58]Gerben Beintema, Roland Tóth, Maarten Schoukens:
Nonlinear state-space identification using deep encoder networks. L4DC 2021: 241-250 - [c57]Ioannis Proimadis, Yorick Broens, Roland Tóth, Hans Butler:
Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system. L4DC 2021: 535-546 - [i43]Patrick J. W. Koelewijn, Roland Tóth:
Incremental Stability and Performance Analysis of Discrete-Time Nonlinear Systems using the LPV Framework. CoRR abs/2103.10819 (2021) - [i42]Hossam S. Abbas, Roland Tóth, Mihály Petreczky, Nader Meskin, Javad Mohammadpour Velni, Patrick J. W. Koelewijn:
LPV Modeling of Nonlinear Systems: A Multi-Path Feedback Linearization Approach. CoRR abs/2103.14622 (2021) - [i41]Chris Verhoek, Hossam S. Abbas, Roland Tóth, Sofie Haesaert:
Data-Driven Predictive Control for Linear Parameter-Varying Systems. CoRR abs/2103.16160 (2021) - [i40]Chris Verhoek, Roland Tóth, Sofie Haesaert, Anne Koch:
Fundamental Lemma for Data-Driven Analysis of Linear Parameter-Varying Systems. CoRR abs/2103.16171 (2021) - [i39]Ruigang Wang, Patrick J. W. Koelwijn, Ian R. Manchester, Roland Tóth:
Nonlinear parameter-varying state-feedback design for a gyroscope using virtual control contraction metrics. CoRR abs/2104.04917 (2021) - [i38]Patrick J. W. Koelewijn, Roland Tóth, Henk Nijmeijer, Siep Weiland:
Nonlinear Tracking and Rejection using Linear Parameter-Varying Control. CoRR abs/2104.09938 (2021) - [i37]Ioannis Proimadis, Yorick Broens, Roland Tóth, Hans Butler:
Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system. CoRR abs/2105.01458 (2021) - [i36]Pascal den Boef, Pepijn B. Cox, Roland Tóth:
LPVcore: MATLAB Toolbox for LPV Modelling, Identification and Control. CoRR abs/2105.03695 (2021) - [i35]Gábor Rödönyi, Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens, Daniel Pup, Ádám Kisari, Zs. Vígh, Péter Korös, Alexandros Soumelidis, József Bokor:
Identification of the nonlinear steering dynamics of an autonomous vehicle. CoRR abs/2105.04529 (2021) - [i34]Clarisse Pétua Bosman Barros, Hans Butler, Roland Tóth:
On the Use of the Smith-McMillan Form in Decoupling System Dynamics. CoRR abs/2105.11885 (2021) - [i33]Tom Bloemers, Roland Tóth, Tom Oomen:
Frequency-Domain Data-Driven Controller Synthesis for Unstable LPV Systems. CoRR abs/2107.09712 (2021) - [i32]Tom Bloemers, Roland Tóth, Tom Oomen:
Frequency Response Data Based LPV Controller Synthesis Applied to a Control Moment Gyroscope. CoRR abs/2109.05774 (2021) - [i31]Patrick J. W. Koelewijn, Roland Tóth, Siep Weiland:
Incremental Dissipativity based Control of Discrete-Time Nonlinear Systems via the LPV Framework. CoRR abs/2110.00290 (2021) - [i30]Lucian-Cristian Iacob, Gerben Izaak Beintema, Maarten Schoukens, Roland Tóth:
Deep Identification of Nonlinear Systems in Koopman Form. CoRR abs/2110.02583 (2021) - [i29]Yuhan Liu, Roland Tóth:
Learning Based Model Predictive Control for Quadcopters with Dual Gaussian Process. CoRR abs/2112.11667 (2021) - 2020
- [j26]Jurre Hanema, Mircea Lazar, Roland Tóth:
Heterogeneously parameterized tube model predictive control for LPV systems. Autom. 111 (2020) - [j25]Vincent Laurain, Roland Tóth, Dario Piga, Mohamed Abdelmonim Hassan Darwish:
Sparse RKHS estimation via globally convex optimization and its application in LPV-IO identification. Autom. 115: 108914 (2020) - [j24]Dhruv Khandelwal, Maarten Schoukens, Roland Tóth:
A Tree Adjoining Grammar representation for models of stochastic dynamical systems. Autom. 119: 109099 (2020) - [c56]Patrick J. W. Koelewijn, Roland Tóth:
Scheduling Dimension Reduction of LPV Models - A Deep Neural Network Approach. ACC 2020: 1111-1117 - [c55]Zechen Liu, Zizhang Wu, Roland Tóth:
SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation. CVPR Workshops 2020: 4289-4298 - [c54]P. J. W. Koelewijn, G. Sales Mazzoccante, Roland Tóth, Siep Weiland:
Pitfalls of Guaranteeing Asymptotic Stability in LPV Control of Nonlinear Systems. ECC 2020: 1573-1578 - [i28]Dhruv Khandelwal, Maarten Schoukens, Roland Tóth:
A Tree Adjoining Grammar Representation for Models Of Stochastic Dynamical Systems. CoRR abs/2001.05320 (2020) - [i27]Zechen Liu, Zizhang Wu, Roland Tóth:
SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation. CoRR abs/2002.10111 (2020) - [i26]Ruigang Wang, Roland Tóth, Ian R. Manchester:
Virtual Control Contraction Metrics: Convex Nonlinear Feedback Design via Behavioral Embedding. CoRR abs/2003.08513 (2020) - [i25]Maarten Schoukens, Roland Tóth:
On the Initialization of Nonlinear LFR Model Identification with the Best Linear Approximation. CoRR abs/2004.05040 (2020) - [i24]P. J. W. Koelewijn, G. Sales Mazzoccante, Roland Tóth, Siep Weiland:
Pitfalls of Guaranteeing Asymptotic Stability in LPV Control of Nonlinear Systems. CoRR abs/2004.13370 (2020) - [i23]P. J. W. Koelewijn, Roland Tóth:
Scheduling Dimension Reduction of LPV Models - A Deep Neural Network Approach. CoRR abs/2005.06786 (2020) - [i22]Chris Verhoek, Patrick J. W. Koelewijn, Roland Tóth:
Convex Incremental Dissipativity Analysis of Nonlinear Systems. CoRR abs/2006.14201 (2020) - [i21]Pepijn B. Cox, Roland Tóth:
Linear Parameter-Varying Subspace Identification: A Unified Framework. CoRR abs/2008.03347 (2020) - [i20]Arash Sadeghzadeh, Bardia Sharif, Roland Tóth:
Affine Linear Parameter-Varying Embedding of Nonlinear Models with Improved Accuracy and Minimal Overbounding. CoRR abs/2010.01500 (2020) - [i19]Arash Sadeghzadeh, Roland Tóth:
Linear Parameter-Varying Embedding of Nonlinear Models with Reduced Conservativeness. CoRR abs/2011.03496 (2020) - [i18]Gerben Beintema, Roland Tóth, Maarten Schoukens:
Nonlinear state-space identification using deep encoder networks. CoRR abs/2012.07697 (2020) - [i17]Gerben Izaak Beintema, Roland Tóth, Maarten Schoukens:
Non-linear State-space Model Identification from Video Data using Deep Encoders. CoRR abs/2012.07721 (2020) - [i16]Stefan-Cristian Nechita, Roland Tóth, Dhruv Khandelwal, Maarten Schoukens:
Toolbox for Discovering Dynamic System Relations via TAG Guided Genetic Programming. CoRR abs/2012.08834 (2020)
2010 – 2019
- 2019
- [c53]Tom Bloemers, Roland Tóth, Tom Oomen:
Towards Data-Driven LPV Controller Synthesis Based on Frequency Response Functions. CDC 2019: 5680-5685 - [c52]Dhruv Khandelwal, Maarten Schoukens, Roland Tóth:
Data-driven Modelling of Dynamical Systems Using Tree Adjoining Grammar and Genetic Programming. CEC 2019: 2673-2680 - [c51]Manas Mejari, Dario Piga, Roland Tóth, Alberto Bemporad:
Kernelized Identification of Linear Parameter-Varying Models with Linear Fractional Representation. ECC 2019: 337-342 - [c50]Dhruv Khandelwal, Maarten Schoukens, Roland Tóth:
Grammar-based Representation and Identification of Dynamical Systems. ECC 2019: 1318-1323 - [i15]Dhruv Khandelwal, Maarten Schoukens, Roland Tóth:
Data-driven Modelling of Dynamical Systems Using Tree Adjoining Grammar and Genetic Programming. CoRR abs/1904.03152 (2019) - [i14]Ruigang Wang, Roland Tóth, Ian R. Manchester:
A Comparison of LPV Gain Scheduling and Control Contraction Metrics for Nonlinear Control. CoRR abs/1905.01811 (2019) - [i13]P. J. W. Koelewijn, Roland Tóth, Henk Nijmeijer:
Linear Parameter-Varying Control of Nonlinear Systems based on Incremental Stability. CoRR abs/1909.07154 (2019) - [i12]Jurre Hanema, Mircea Lazar, Roland Tóth:
Heterogeneously parameterized tube model predictive control for LPV systems. CoRR abs/1910.08449 (2019) - 2018
- [j23]Mohamed Abdelmonim Hassan Darwish, Gianluigi Pillonetto, Roland Tóth:
The quest for the right kernel in Bayesian impulse response identification: The use of OBFs. Autom. 87: 318-329 (2018) - [j22]Syed Zeeshan Rizvi, Javad Mohammadpour Velni, Farshid Abbasi, Roland Tóth, Nader Meskin:
State-space LPV model identification using kernelized machine learning. Autom. 88: 38-47 (2018) - [j21]Mohamed Abdelmonim Hassan Darwish, Pepijn Bastiaan Cox, Ioannis Proimadis, Gianluigi Pillonetto, Roland Tóth:
Prediction-error identification of LPV systems: A nonparametric Gaussian regression approach. Autom. 97: 92-103 (2018) - [j20]Pepijn Bastiaan Cox, Roland Tóth, Mihály Petreczky:
Towards efficient maximum likelihood estimation of LPV-SS models. Autom. 97: 392-403 (2018) - [j19]Pepijn B. Cox, Siep Weiland, Roland Tóth:
Affine Parameter-Dependent Lyapunov Functions for LPV Systems With Affine Dependence. IEEE Trans. Autom. Control. 63(11): 3865-3872 (2018) - [c49]T. A. H. Bloemers, Ioannis Proimadis, Yanin Kasemsinsup, Roland Tóth:
Parameter-Dependent Feedforward Strategies for Motion Systems. ACC 2018: 2017-2022 - [c48]Dhruv Khandelwal, Maarten Schoukens, Roland Tóth:
On the Simulation of Polynomial NARMAX Models. CDC 2018: 1445-1450 - [i11]Tom Bloemers, Ioannis Proimadis, Yanin Kasemsinsup, Roland Tóth:
Feedforward Control of Magnetically Levitated Planar Actuators. CoRR abs/1802.09361 (2018) - [i10]Pepijn B. Cox, Siep Weiland, Roland Tóth:
Affine Parameter-Dependent Lyapunov Functions for LPV Systems with Affine Dependence. CoRR abs/1803.11543 (2018) - [i9]Pepijn B. Cox, Roland Tóth, Mihály Petreczky:
Towards Efficient Maximum Likelihood Estimation of LPV-SS Models. CoRR abs/1808.01633 (2018) - [i8]Maarten Schoukens, Roland Tóth:
From Nonlinear Identification to Linear Parameter Varying Models: Benchmark Examples. CoRR abs/1809.05000 (2018) - [i7]Maarten Schoukens, Roland Tóth:
Linear Parameter Varying Representation of a class of MIMO Nonlinear Systems. CoRR abs/1809.05011 (2018) - [i6]Dhruv Khandelwal, Maarten Schoukens, Roland Tóth:
On the Simulation of Polynomial NARMAX Models. CoRR abs/1810.06883 (2018) - [i5]Dhruv Khandelwal, Maarten Schoukens, Roland Tóth:
Grammar-based Representation and Identification of Dynamical Systems. CoRR abs/1811.10576 (2018) - 2017
- [j18]Simon Wollnack, Hossam Seddik Abbas, Roland Tóth, Herbert Werner:
Fixed-structure LPV-IO controllers: An implicit representation based approach. Autom. 83: 282-289 (2017) - [j17]Jurre Hanema, Mircea Lazar, Roland Tóth:
Stabilizing tube-based model predictive control: Terminal set and cost construction for LPV systems. Autom. 85: 137-144 (2017) - [j16]Mihály Petreczky, Roland Tóth, Guillaume Mercère:
Realization Theory for LPV State-Space Representations With Affine Dependence. IEEE Trans. Autom. Control. 62(9): 4667-4674 (2017) - [j15]Arash Golabi, Nader Meskin, Roland Tóth, Javad Mohammadpour:
A Bayesian Approach for LPV Model Identification and Its Application to Complex Processes. IEEE Trans. Control. Syst. Technol. 25(6): 2160-2167 (2017) - [c47]Shaikshavali Chitraganti, Roland Tóth, Nader Meskin, Javad Mohammadpour:
Stochastic model predictive control for LPV systems. ACC 2017: 5654-5659 - [c46]Erik Schulz, Pepijn B. Cox, Roland Tóth, Herbert Werner:
LPV state-space identification via IO methods and efficient model order reduction in comparison with subspace methods. CDC 2017: 3575-3581 - [c45]Jurre Hanema, Roland Tóth, Mircea Lazar:
Stabilizing non-linear MPC using linear parameter-varying representations. CDC 2017: 3582-3587 - [i4]Jurre Hanema, Mircea Lazar, Roland Tóth:
Stabilizing Tube-Based Model Predictive Control: Terminal Set and Cost Construction for LPV Systems (extended version). CoRR abs/1702.05393 (2017) - 2016
- [j14]Simone Formentin, Dario Piga, Roland Tóth, Sergio M. Savaresi:
Direct learning of LPV controllers from data. Autom. 65: 98-110 (2016) - [j13]Hossam S. Abbas, Roland Tóth, Nader Meskin, Javad Mohammadpour, Jurre Hanema:
A Robust MPC for Input-Output LPV Models. IEEE Trans. Autom. Control. 61(12): 4183-4188 (2016) - [j12]Syed Zeeshan Rizvi, Javad Mohammadpour, Roland Tóth, Nader Meskin:
A Kernel-Based PCA Approach to Model Reduction of Linear Parameter-Varying Systems. IEEE Trans. Control. Syst. Technol. 24(5): 1883-1891 (2016) - [c44]Jurre Hanema, Roland Tóth, Mircea Lazar, Hossam S. Abbas:
MPC for linear parameter-varying systems in input-output representation. ISIC 2016: 1-6 - [c43]Arash Golabi, Nader Meskin, Roland Tóth, Javad Mohammadpour, Tijs Donkers:
Event-triggered control for discrete-time linear parameter-varying systems. ACC 2016: 3680-3685 - [c42]Qin Liu, Javad Mohammadpour, Roland Tóth, Nader Meskin:
Non-parametric identification of linear parameter-varying spatially-interconnected systems using an LS-SVM approach. ACC 2016: 4592-4597 - [c41]Pepijn B. Cox, Roland Tóth:
LPV State-space model identification in the Bayesian setting: A 3-step procedure. ACC 2016: 4604-4610 - [c40]Pepijn Bastiaan Cox, Roland Tóth:
Alternative form of predictor based identification of LPV-SS models with innovation noise. CDC 2016: 1223-1228 - [c39]Jurre Hanema, Roland Tóth, Mircea Lazar:
Tube-based anticipative model predictive control for linear parameter-varying systems. CDC 2016: 1458-1463 - [c38]Arash Golabi, Mohammad Reza Davoodi, Nader Meskin, Javad Mohammadpour, Roland Tóth:
Event-triggered fault detection for discrete-time LPV systems. EBCCSP 2016: 1-8 - [i3]Pepijn B. Cox, Roland Tóth:
Alternative Form of Predictor Based Identification of LPV-SS Models with Innovation Noise. CoRR abs/1609.07536 (2016) - [i2]Pepijn Bastiaan Cox, Roland Tóth:
On the Connection Between Different Noise Structures for LPV-SS Models. CoRR abs/1610.09173 (2016) - 2015
- [j11]Dario Piga, Pepijn B. Cox, Roland Tóth, Vincent Laurain:
LPV system identification under noise corrupted scheduling and output signal observations. Autom. 53: 329-338 (2015) - [j10]Vincent Laurain, Roland Tóth, Dario Piga, Wei Xing Zheng:
An instrumental least squares support vector machine for nonlinear system identification. Autom. 54: 340-347 (2015) - [c37]Sandy Rahme, Hossam S. Abbas, Nader Meskin, Roland Tóth, Javad Mohammadpour:
Reduced LPV model development and control of a solution copolymerization reactor. CCA 2015: 1044-1050 - [c36]Wallace E. Larimore, Pepijn B. Cox, Roland Tóth:
CVA identification of nonlinear systems with LPV state-space models of affine dependence. ACC 2015: 831-837 - [c35]Mohamed Abdelmonim Hassan Darwish, Pepijn B. Cox, Gianluigi Pillonetto, Roland Tóth:
Bayesian identification of LPV Box-Jenkins models. CDC 2015: 66-71 - [c34]Hossam S. Abbas, Roland Tóth, Nader Meskin, Javad Mohammadpour, Jurre Hanema:
An MPC approach for LPV systems in input-output form. CDC 2015: 91-96 - [c33]Farshid Abbasi, Javad Mohammadpour, Roland Tóth, Nader Meskin:
A Bayesian approach for model identification of LPV systems with uncertain scheduling variables. CDC 2015: 789-794 - [c32]Mohamed Abdelmonim Hassan Darwish, Gianluigi Pillonetto, Roland Tóth:
Perspectives of orthonormal basis functions based kernels in Bayesian system identification? CDC 2015: 2713-2718 - [c31]A. A. Bachnas, Siep Weiland, Roland Tóth:
Data driven predictive control based on orthonormal basis functions. CDC 2015: 3026-3031 - [c30]Mert Bastug, Mihály Petreczky, Roland Tóth, Rafael Wisniewski, John Leth, Denis V. Efimov:
Moment matching based model reduction for LPV state-space models. CDC 2015: 5334-5339 - [c29]Syed Zeeshan Rizvi, Javad Mohammadpour, Roland Tóth, Nader Meskin:
An IV-SVM-based approach for identification of state-space LPV models under generic noise conditions. CDC 2015: 7380-7385 - [i1]Mert Bastug, Mihály Petreczky, Roland Tóth, Rafael Wisniewski, John Leth, Denis V. Efimov:
Moment Matching Based Model Reduction for LPV State-Space Models. CoRR abs/1508.03446 (2015) - 2014
- [j9]Dario Piga, Roland Tóth:
A bias-corrected estimator for nonlinear systems with output-error type model structures. Autom. 50(9): 2373-2380 (2014) - [j8]Cristian R. Rojas, Roland Tóth, Håkan Hjalmarsson:
Sparse Estimation of Polynomial and Rational Dynamical Models. IEEE Trans. Autom. Control. 59(11): 2962-2977 (2014) - [c28]Arash Golabi, Nader Meskin, Roland Tóth, Javad Mohammadpour:
A Bayesian approach for estimation of linear-regression LPV models. CDC 2014: 2555-2560 - [c27]Rene Duijkers, Roland Tóth, Dario Piga, Vincent Laurain:
Shrinking complexity of scheduling dependencies in LS-SVM based LPV system identification. CDC 2014: 2561-2566 - [c26]Farshid Abbasi, Javad Mohammadpour, Roland Tóth, Nader Meskin:
A support vector machine-based method for LPV-ARX identification with noisy scheduling parameters. ECC 2014: 370-375 - [c25]Syed Zeeshan Rizvi, Javad Mohammadpour, Roland Tóth, Nader Meskin:
Parameter Set-mapping using kernel-based PCA for linear parameter-varying systems. ECC 2014: 2744-2749 - 2013
- [j7]Dario Piga, Roland Tóth:
An SDP approach for l0-minimization: Application to ARX model segmentation. Autom. 49(12): 3646-3653 (2013) - [c24]Simon Wollnack, Hossam S. Abbas, Herbert Werner, Roland Tóth:
Fixed-structure LPV controller synthesis based on implicit input output representations. CDC 2013: 2103-2108 - [c23]Simone Formentin, Dario Piga, Roland Tóth, Sergio M. Savaresi:
Direct data-driven control of linear parameter-varying systems. CDC 2013: 4110-4115 - [c22]Dario Piga, Roland Tóth:
LPV model order selection in an LS-SVM setting. CDC 2013: 4128-4133 - [c21]A. A. Bachnas, Roland Tóth, Ali Mesbah, Jobert H. A. Ludlage:
Perspectives of data-driven LPV modeling of high-purity distillation columns. ECC 2013: 3776-3783 - 2012
- [j6]Roland Tóth, Vincent Laurain, Marion Gilson, Hugues Garnier:
Instrumental variable scheme for closed-loop LPV model identification. Autom. 48(9): 2314-2320 (2012) - [j5]Roland Tóth, Hossam Seddik Abbas, Herbert Werner:
On the State-Space Realization of LPV Input-Output Models: Practical Approaches. IEEE Trans. Control. Syst. Technol. 20(1): 139-153 (2012) - [j4]Roland Tóth, Marco Lovera, Peter S. C. Heuberger, Matteo Corno, Paul M. J. Van den Hof:
On the Discretization of Linear Fractional Representations of LPV Systems. IEEE Trans. Control. Syst. Technol. 20(6): 1473-1489 (2012) - [c20]Vito Cerone, Dario Piga, Diego Regruto, Roland Tóth:
Minimal LPV state-space realization driven set-membership identification. ACC 2012: 3421-3426 - [c19]Roland Tóth, Håkan Hjalmarsson, Cristian R. Rojas:
Order and structural dependence selection of LPV-ARX models revisited. CDC 2012: 6271-6276 - [c18]Muhammad Mohsin Siraj, Roland Tóth, Siep Weiland:
Joint order and dependency reduction for LPV state-space models. CDC 2012: 6291-6296 - [c17]Vito Cerone, Dario Piga, Diego Regruto, Roland Tóth:
Fixed order LPV controller design for LPV models in input-output form. CDC 2012: 6297-6302 - 2011
- [j3]Roland Tóth, Jan C. Willems, Peter S. C. Heuberger, Paul M. J. Van den Hof:
The Behavioral Approach to Linear Parameter-Varying Systems. IEEE Trans. Autom. Control. 56(11): 2499-2514 (2011) - [c16]Roland Tóth, Marc van de Wal, Peter S. C. Heuberger, Paul M. J. Van den Hof:
LPV identification of high performance positioning devices. ACC 2011: 151-158 - [c15]Vincent Laurain, Marion Gilson, Roland Tóth, Hugues Garnier:
Direct identification of continuous-time LPV models. ACC 2011: 159-164 - [c14]Roland Tóth, Borhan Molazem Sanandaji, Kameshwar Poolla, Tyrone L. Vincent:
Compressive System Identification in the Linear Time-Invariant framework. CDC/ECC 2011: 783-790 - [c13]Borhan Molazem Sanandaji, Tyrone L. Vincent, Michael B. Wakin, Roland Tóth, Kameshwar Poolla:
Compressive System Identification of LTI and LTV ARX models. CDC/ECC 2011: 791-798 - [c12]Arne G. Dankers, Roland Tóth, Peter S. C. Heuberger, Xavier Bombois, Paul M. J. Van den Hof:
Informative data and identifiability in LPV-ARX prediction-error identification. CDC/ECC 2011: 799-804 - [c11]Roland Tóth, Vincent Laurain, Wei Xing Zheng, Kameshwar Poolla:
Model structure learning: A support vector machine approach for LPV linear-regression models. CDC/ECC 2011: 3192-3197 - [c10]Vincent Laurain, Wei Xing Zheng, Roland Tóth:
Introducing instrumental variables in the LS-SVM based identification framework. CDC/ECC 2011: 3198-3203 - 2010
- [j2]Vincent Laurain, Marion Gilson, Roland Tóth, Hugues Garnier:
Refined instrumental variable methods for identification of LPV Box-Jenkins models. Autom. 46(6): 959-967 (2010) - [c9]Vincent Laurain, Marion Gilson, Roland Tóth, Hugues Garnier:
Identification of LPV output-error and Box-Jenkins models via optimal refined instrumental variable methods. ACC 2010: 3865-3870 - [c8]Hossam S. Abbas, Roland Tóth, Herbert Werner:
State-Space realization of LPV Input-Output models: practical methods for the user. ACC 2010: 3883-3888
2000 – 2009
- 2009
- [j1]Roland Tóth, Peter S. C. Heuberger, Paul M. J. Van den Hof:
Asymptotically optimal orthonormal basis functions for LPV system identification. Autom. 45(6): 1359-1370 (2009) - [c7]Roland Tóth, Christian Lyzell, Martin Enqvist, Peter S. C. Heuberger, Paul M. J. Van den Hof:
Order and structural dependence selection of LPV-ARX models using a nonnegative garrote approach. CDC 2009: 7406-7411 - [c6]Roland Tóth, Marco Lovera, Peter S. C. Heuberger, Paul M. J. Van den Hof:
Discretization of Linear Fractional Representations of LPV systems. CDC 2009: 7424-7429 - [c5]Roland Tóth, Jan C. Willems, Peter S. C. Heuberger, Paul M. J. Van den Hof:
A behavioral approach to LPV systems. ECC 2009: 2015-2020 - 2008
- [c4]Roland Tóth, Peter S. C. Heuberger, Paul M. J. Van den Hof:
Flexible model structures for LPV identification with static scheduling dependency. CDC 2008: 4522-4527 - 2007
- [c3]Roland Tóth, Peter S. C. Heuberger, Paul M. J. Van den Hof:
LPV system identification with globally fixed orthonormal basis functions. CDC 2007: 3646-3653 - 2006
- [c2]Roland Tóth, Peter S. C. Heuberger, Paul M. J. Van den Hof:
Orthonormal basis selection for LPV system identification, the Fuzzy-Kolmogorov c-Max approach. CDC 2006: 2529-2534 - 2004
- [c1]Denes Fodor, Roland Tóth:
Speed sensorless linear parameter variant H∞ control of the induction motor. CDC 2004: 4435-4440
Coauthor Index
Hossam S. Abbas
aka: Hossam Seddik Abbas
aka: Hossam Seddik Abbas
Gerben Beintema
aka: Gerben Izaak Beintema
aka: Gerben Izaak Beintema
Pepijn B. Cox
aka: Pepijn Bastiaan Cox
aka: Pepijn Bastiaan Cox
P. J. W. Koelewijn
aka: Patrick J. W. Koelewijn
aka: Patrick J. W. Koelewijn
Javad Mohammadpour
aka: Javad Mohammadpour Velni
aka: Javad Mohammadpour Velni
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