Publications

Book

  1. Tóth, R.: Modeling and identification of linear parameter-varying systems. Lecture Notes in Control and Information Sciences, Vol. 403, Springer, Heidelberg, 2010. (book webpage) (link)

Book Chapters (4)

  1. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof:  Prediction error identification of LPV systems: present and beyond. In: J. Mohammadpour and C. W. Scherer (Eds.), Control of Linear Parameter Varying Systems with Applications (pp. 27-60), Springer, Heidelberg, 2012. (pdf) (link)
  2. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof:  LPV system identification using series-expansion models. In: P. L. dos Santos, C. Novara, D. Rivera, J. Ramos and T-P. Perdicoúlis (Eds.), Linear Parameter-Varying System Identification: New Developments and Trends (pp. 259-294), World Scientific Publishing, Singapore, 2011. (pdf) (link)
  3. Laurain, V., M. Gilson, H. Garnier, R. Tóth:  Identification of discrete-time and continuous-time input/output LPV models. In: P. L. dos Santos, C. Novara, D. Rivera, J. Ramos and T-P. Perdicoúlis (Eds.), Linear Parameter-Varying System Identification: New Developments and Trends (pp. 95-132), World Scientific Publishing, Singapore, 2011. (pdf) (link)
  4. Van den Hof, P. M. J., R. Tóth and P. S. C. Heuberger: Model structures for identification of linear parameter-varying (LPV) models, In: K. M. Hangos and L. Nádai (Ed.). Proceedings of the Workshop on Systems and Control Theory in honor of József Bokor on his 60th Birthday (pp. 15-34), MTA, Budapest, 2009. (pdf)

Journal Papers (34)

  1. Darwish , M. A. H., P. B. Cox, I. Proimadis, G. Pillonetto and R. Tóth:  Prediction-Error Identification of LPV Systems: A Nonparametric Gaussian Regression Approach, Automatica, Vol. 97, (2018), pp. 92-103. (pdf) (link)
  2. Cox, P. B., R. Tóth, M. Petreczky: Towards Efficient Maximum Likelihood Estimation of LPV-SS Models, Automatica, Vol. 97, (2018), pp 392-403. (ERC(pdf) (data) (link) (arXiv)
  3. Cox, P. B., S. Weiland and R. Tóth: Affine Parameter-Dependent Lyapunov Functions for LPV Systems with Affine Dependence, IEEE Transactions on Automatic Control, Vol. 63, No. 11, (2018), pp. 3865-3872. (ERC) (pdf) (link) (arxiv)
  4. Rizvi, S.Z., J. Mohammadpour, F. Abbasi, R. Tóth and  M. Meskin: State-space LPV Model Identification Using Kernelized Machine Learning, Automatica, Vol. 88, (2018), pp. 38-47. (pdf) (link)
  5. Abbas, H. S., J. Hanema, R. Tóth, N. Meskin, and J. Mohammadpour: An Improved Robust Model Predictive Control for Linear Parameter-Varying Input-Output Models, International Journal of Robust and Nonlinear Control, Vol. 28, No. 3, (2018), pp. 859-880. (pdf) (link)
  6. Darwish , M. A. H., G. Pillonetto and R. Tóth: The Quest for the Right Kernel in Bayesian Impulse Response Identification: The Use of OBFs, Automatica, Vol. 87, (2018), pp. 318-329. (pdf) (link)
  7. Golabi, A., N. Meskin, R. Tóth, J. Mohammadpour and T. Donkers: Event-triggered Reference Tracking Control for Discrete-time LPV Systems with Application to a Laboratory Tank System, IET Control Theory & Applications, Vol. 11, No. 16, (2017), pp. 2680-2687. (pdf) (link)
  8. Hanema, J., M. Lazar and R. Tóth: Stabilizing Tube-Based Model Predictive Control for LPV Systems,  Automatica, Vol. 85, (2017), pp. 137–144. (pdf) (link)
  9. Wollnack, S., H. S. Abbas, H. Werner, and R. Tóth: Fixed-Structure LPV-IO Controllers: An Implicit Representation Based Approach, Automatica, Vol. 83. (2017), pp 282–289. (pdf) (link)
  10. Chitraganti, S., R. Tóth, N. Meskin and J. Mohammadpour: Stochastic model predictive tracking of piecewise constant references for LPV systems, IET Control Theory & Applications, Vol. 11, No. 12, (2017), pp 1862-1872. (pdf) (link)
  11. Golabi, A., N. Meskin, R. Tóth  and J. Mohammadpour: A Bayesian Approach for LPV Model Identification and its Application to Complex Chemical Processes, IEEE Transactions on Control Systems Technology, Vol. 25, No. 6, (2017), pp. 2160-2167. (pdf) (link)
  12. Petreczky, M., R. Tóth and G. Mercere: Realization Theory for LPV State-Space Representations with Affine Dependence, IEEE Transactions on Automatic Control, Vol. 62, No. 9, (2017), pp. 4667-4674. (pdf) (link)
  13. Lataire, J., R. Pintelon, D. Piga, and R. Tóth: Continuous-Time Linear Time-Varying System Identification with a Frequency-Domain Kernel Based Estimator, IET Control Theory & Applications, Vol. 11, No. 4, (2017), pp. 457-465. (pdf) (link)
  14. Abbas, H. S., R. Tóth, N. Meskin, J. Mohammadpour, J. Hanema: A Robust MPC for Input-Output LPV Models, IEEE Transactions on Automatic Control, Vol. 61, No. 12, (2016). (pdf) (link)
  15. Rahme, S., H. S. Abbas, N. Meskin, R. Tóth  and J. Mohammadpour: LPV Model Development and Control of A Solution Copolymerization Reactor, Control Engineering Practice, Vol. 48, (2016), pp. 98-110. (pdf) (link)
  16. Rizvi, S.Z., J. Mohammadpour, R. Tóth and N. Meskin: A Kernel-based PCA Approach to Model Reduction of Linear Parameter-varying Systems, IEEE Transactions on Control Systems Technology, Vol. 24, (2016), pp. 1883-1891. (pdf) (link)
  17. Formentin, S., D. Piga, R. Tóth, S. Savaresi: Direct learning of LPV controllers from data, Automatica, Vol. 65, (2016), pp. 98-110. (pdf) (link)
  18. Verbert, K. A. J., R. Tóth and R. Babuška: Adaptive Friction Compensation: A Globally Stable Approach, IEEE/ASME Transactions on Mechatronics, Vol. 21, No. 1, (2016), pp. 351-363. (pdf) (link)
  19. Laurain, V., R. Tóth, D. Piga, W. X. Zheng: An Instrumental Least Squares Support Vector Machine for Nonlinear System Identification, Automatica, Vol. 54, (2015), pp 340-347. (pdf) (link)
  20. Piga, D., P. Cox, R. Tóth and V. Laurain: LPV system identification under noise corrupted scheduling and output signal observations, Automatica , Vol. 53, (2015), pp. 329-338. (pdf) (link)
  21. Rojas, C. R., R. Tóth and H. Hjalmarsson: Sparse estimation of polynomial and rational dynamic models, special issue, IEEE Transactions on Automatic Control, Vol. 59, No. 11, (2014), pp. 2962-2977. (pdf) (link)
  22. Piga, D. and R. Tóth: A bias-corrected estimator for nonlinear systems with output-error type model structures, Automatica, Vol. 50, No. 9, (2014), pp. 2373-2380. (pdf) (link)
  23. Bachnas, A. A., R. Tóth, A. Mesbah, J. H. A. Ludlage: A review on data-driven linear parameter-varying modeling approaches: A high-purity distillation column case study, Journal of Process Control, Vol. 24, No. 4, (2014), pp. 272–285. (pdf) (errata) (link)
  24. Piga, D. and R. Tóth: An SDP approach for l_0-minimization: application to ARX model segmentation, Automatica, Vol. 49, No. 12, (2013), pp. 3646–3653. (pdf) (link)
  25. Tóth, R., V. Laurain, M. Gilson and H. Garnier: Instrumental variable scheme for closed-loop LPV model identification, Automatica, Vol. 48, No. 9, (2012), pp. 2314-2320. (pdf) (link)
  26. Tóth, R., M. Lovera, P. S. C. Heuberger, M. Corno and P. M. J. Van den Hof: On the discretization of linear fractional representations of LPV systems, IEEE Transactions on Control Systems Technology, Vol. 20, No. 6, (2012), pp. 1473-1489. (pdf) (link) (tech report)
  27. Tóth, R., H. Abbas and H. Werner: On the state-space realization of LPV input-output models: practical approaches, IEEE Transactions on Control Systems Technology, Vol. 20, No. 1, (2012), pp. 139-153. (pdf) (errata) (link)
  28. Laurain, V., R. Tóth, M. Gilson and H. Garnier: Direct identification of continuous-time LPV input/output models, special issue, IET Control Theory & Applications, Vol. 5, No. 7, (2011), pp. 878-888. (pdf) (link)
  29. Tóth, R., J. C. Willems, P. S. C. Heuberger and P. M. J. Van den Hof: The behavioral approach to linear parameter-varying systems, IEEE Transactions on Automatic Control, Vol. 56, No. 11, (2011), pp. 2499-2514. (pdf) (link)
  30. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: Discretisation of linear parameter-varying state-space representations, IET Control Theory & Applications, Vol. 4, No. 10, (2010), pp. 2082-2096. (pdf) (link)
  31. Laurain, V., M. Gilson, R. Tóth and H. Garnier: Refined instrumental variable methods for identification of LPV Box-Jenkins models, Automatica, Vol. 46, No. 6, (2010), pp. 959-967. (pdf) (errata) (link)
  32. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: Asymptotically optimal orthonormal basis functions for LPV system Identification, Automatica, Vol. 45, No. 6, (2009), pp. 1359-1370. (pdf) (link)
  33. Tóth, R. and D. Fodor: Speed sensorless mixed sensitivity linear parameter variant H_inf control of the induction motor, Journal of Electrical Engineering, Vol. 6, No. 4, (2006), pp. 12/1-6. (link)
  34. Tóth, R.: Simulation results on the asymptotic periodicity of compartmental systems with lags, Functional Differential Equations, Vol. 11, No. 1-2, (2004), pp. 195-202. (pdf) (link)

Submitted Journal Papers (5)

  1. Abbas, H. S., R. Tóth, M. Petreczky, N. Meskin, and J. Mohammadpour: LPV Modeling of Nonlinear Systems: A Multi-Path Feedback Linearisation Approach, Submitted to the International Journal of Robust and Nonlinear Control (2017).  (pdf is available upon request)
  2. Laurain, V., R. Tóth, D. Piga, M.A.H. Darwish: Model Structure Selection learning for LPV-IO identification: An RKHS approach, Submitted to Automatica (2018) (pdf is available upon request)
  3. Hanema, J., M. Lazar and R. Tóth: Heterogeneously parameterized tube model predictive control for LPV systems, Submitted to Automatica (2018) (pdf is available upon request).
  4. Khandelwal, D. and R. Tóth: An Evolutionary Computation Approach to Identification of Linear Dynamical Systems from Data, Submitted to the IEEE Transactions on Evolutionary Computation (2018).  (pdf is available upon request)
  5. Zou, J., L. Waeijen, D. Goswami and R. Tóth: Robust Active Disturbance Rejection Control Scheme for Quadrotor UAVs: Experimental Prototyping, Submitted to the IEEE Transactions on Industrial Electronics (2018) (pdf is available upon request)

Conference Proceedings (74)

  1. Khandelwal, D., M. Schoukens and R. Tóth: On the Simulation of Polynomial NARMAX Models, Accepted to the 57th IEEE Conference on Decision and Control, (2018), Miami Beach, FL, USA. (CADUSY) (arxiv)
  2. Wiel, T. T. R. van de, R. Tóth and V. I. Kiriouchine: Comparison of Parameter-Varying Decoupling Based Control Schemes for a Quadcopter, Proc. of the IFAC Workshop on Linear Parameter Varying Systems, (2018), Florianopolis, Brazil, pp. 156-162. (ERC)
  3. Koelewijn, P. J. W., P. S. G. Cisneros, H. Werner and R. Tóth: LPV Control of a Gyroscope with Inverted Pendulum Attachment, Proc. of the IFAC Workshop on Linear Parameter Varying Systems, (2018), Florianopolis, Brazil, pp. 150-155. (ERC)
  4. Abbas, H. S., J. Hanema, R. Tóth, J. Mohammadpour and N. Meskin: A New Approach to Robust MPC Design for LPV Systems in Input-Output Form, Proc. of the IFAC Workshop on Linear Parameter Varying Systems, (2018), Florianopolis, Brazil, pp. 392-397.
  5. Schoukens, M. and R. Tóth: Linear Parameter Varying Representation of a class of MIMO Nonlinear Systems, Proc. of the IFAC Workshop on Linear Parameter Varying Systems, (2018), Florianopolis, Brazil, pp. 271-276. (ERC) (pdf) (script) (arxiv)
  6. Bloemers, T.A.H., I.Proimadis, Y. Kasemsinsup and R. Tóth: Position-Dependent Feedforward Strategies for Rigid-Body Motion Systems, Proc. of the American Control Conference, (2018) Milwaukee, WI, USA, pp. 2017-2022. (NAPAS) (pdf) (link)
  7. Schoukens, M. and R. Tóth: From Nonlinear Identification to Linear Parameter Varying Models: Benchmark Examples, Proc. of the IFAC Symposium on System Identification, (2018), Stockholm, Sweden, pp. 419-424. (ERC) (pdf) (link) (arxiv)
  8. Hanema, J., R. Tóth, M. Lazar: Stabilizing Non-linear MPC using Linear Parameter-Varying Representations, Proc. of the 56th IEEE Conference on Decision and Control, (2017), Melbourne, Australia, pp. 3582-3587. (pdf) (link)
  9. Schulz, E., P. B. Cox, H. Werner, R. Tóth: Comparison of IO Structure Assisted State-Space Identification with Subspace Methods for Linear Parameter-Varying Systems, Proc. of the 56th IEEE Conference on Decision and Control, (2017), Melbourne, Australia, pp. 3575-3581. (pdf) (link)
  10. Darwish, M.A.H., J. Lataire and R. Tóth: Bayesian Frequency Domain Identification of LTI Systems with OBFs Kernels, Proc. of the 20th IFAC World Congress, (2017), Toulouse, France, pp. 6412-6417. (pdf) (link)
  11. Hanema, J., M. Lazar and R. Tóth: Tube-based LPV constant output reference tracking MPC with error bound, Proc. of the 20th IFAC World Congress, (2017), Toulouse, France, pp. 8942-8947. (pdf) (link)
  12. Chitraganti, S., R. Tóth, N. Meskin and J. Mohammadpour: Stochastic model predictive control for LPV systems, Proc. of the American Control Conference, (2017) Seattle, WA, USA, pp. 5654-5659. (pdf) (link)
  13. Hanema, J., R. Tóth, M. Lazar: Tube-based anticipative model predictive control for linear parameter-varying systems, Proc. of the 55th IEEE Conference on Decision and Control, (2016) Las Vegas, USA, pp. 1458-1463. (pdf) (link)
  14. Cox, P. B. and R. Tóth: Alternative Form of Predictor Based Identification of LPV-SS Models with Innovation Noise, Proc. of the 55th IEEE Conference on Decision and Control, (2016) Las Vegas, USA, pp. 1223-1228. (pdf) (link)
  15. Hanema, J., R. Tóth, M. Lazar and H. S. Abbas: MPC for Linear Parameter-Varying Systems in Input-Output Representation, IEEE International Symposium on Intelligent Control, (2016) Buenos Aires, Argentina, pp. 354-359. (pdf) (link)
  16. Golabi, A., M. Davoodi, N. Meskin, R. Tóth and J. Mohammadpour: Event-triggered Fault Detection for Discrete-time LPV Systems, Proc. of the conference on Event-Based Control, Communication and Signal Processing, (2016) Krakow, Poland. (pdf) (link)
  17. Cox, P., R. Tóth and M. Petreczky: LPV State-Space Model Identification in a Bayesian Setting: a 3-step Procedure, Proc. of the American Control Conference, (2016) Boston, MA, USA, pp. 4604-4610. (pdf) (link) (Matlab example)
  18. Golabi, A., N. Meskin, R. Tóth, J. Mohammadpour and T. Donkers: Event-triggered Control for Discrete-time LPV Systems, Proc. of the American Control Conference, (2016) Boston, MA, USA, pp. 3680-3685. (pdf) (link)
  19. Liu, Q., J. Mohammadpour, R. Tóth, and N. Meskin: Non-Parametric Identification of Parameter-Varying Spatially-Interconnected Systems Using an LS-SVM Approach, Proc. of the American Control Conference, (2016) Boston, MA, USA, pp. 4592-4597. (pdf) (link)
  20. Baştuğ, M., M. Petreczky, R. Tóth, R. Wisniewski, J. Leth and Denis Efimov: Moment Matching Based Model Reduction for LPV State-Space Models, Proc. of the 54th IEEE Conference on Decision and Control, (2015) Osaka, Japan, pp. 5334-5338. (pdf) (link)
  21. Bachnas, A.A., S. Weiland and R. Tóth: Data Driven Predictive Control Based on OBF Model Structures, Proc. of the 54th IEEE Conference on Decision and Control, (2015) Osaka, Japan, pp. 3026-3031. (pdf) (link)
  22. Abbas, H.S., R. Tóth, Nader Meskin, Javad Mohammadpour and Jurre Hanema: An MPC Approach for LPV Systems in Input-Output Form, Proc. of the 54th IEEE Conference on Decision and Control, (2015) Osaka, Japan, pp. 91-96. (pdf) (link)
  23. Darwish, M., P. Cox, G. Pillonetto and R. Tóth: Bayesian Identification of LPV Box-Jenkins Models, Proc. of the 54th IEEE Conference on Decision and Control, (2015) Osaka, Japan, pp. 66-71. (pdf) (link)
  24. Darwish, M., G. Pillonetto and R. Tóth: Perspectives of Orthonormal Basis Functions Based Kernels in Bayesian System Identification, Proc. of the 54th IEEE Conference on Decision and Control, (2015) Osaka, Japan, pp. 2713-2718. (pdf) (link)
  25. Abbasi, F., J. Mohammadpour, R. Tóth and Nader Meskin: A Bayesian Approach for Model Identification of LPV Systems with Uncertain Scheduling Variables, Proc. of the 54th IEEE Conference on Decision and Control, (2015) Osaka, Japan, pp. 789-794. (pdf) (link)
  26. Rizvi, S. Z., J. Mohammadpour, R. Tóth and Nader Meskin: An IV-SVM-based Approach for Identification of State-space LPV Models under Generic Noise Conditions, Proc. of the 54th IEEE Conference on Decision and Control, (2015) Osaka, Japan, pp. 7380-7385. (pdf) (link)
  27. Rahme, S., H. S. Abbas, N. Meskin, R. Tóth and J. Mohammadpour: Reduced LPV Model Development and Control of a Solution Copolymerization Reactor, Proc. of the IEEE Multi-Conference on Systems and Control, (2015) Sydney, Australia, pp. 1044-1050. (pdf) (link)
  28. Rahme, S., H.S. Abbas, N. Meskin, C. Hoffmann, R. Tóth and J. Mohammadpour: Linear Parameter-Varying Control of a Copolymerization Reactor, Proc. of the 1st IFAC Workshop on Linear Parameter-Varying Systems, (2015) Grenoble, France, pp. 200-206. (pdf) (link)
  29. Rizvi, S.Z., J. Mohammadpour, R. Tóth and N. Meskin: A Kernel-based Approach to MIMO LPV State-space Identification and Application to a Nonlinear Process System Proc. of the 1st IFAC Workshop on Linear Parameter-Varying Systems, (2015) Grenoble, France, pp. 85-90. (pdf) (link)
  30. Cox, P.B., R. Tóth and M. Petreczky: Estimation of LPV-SS Models with Static Dependency using Correlation Analysis, Proc. of the 1st IFAC Workshop on Linear Parameter-Varying Systems, (2015) Grenoble, France, pp. 91-96. (pdf) (link)
  31. Formentin, S., D. Piga, R. Tóth and S. Savaresi: Nonparametric LPV data-driven control, Proc. of the 1st IFAC Workshop on Linear Parameter-Varying Systems, (2015) Grenoble, France, pp. 146-151. (pdf) (link)
  32. Larimore, W.E., P.B. Cox, R. Tóth: CVA Identification of Nonlinear Systems with LPV State-Space Models of Affine Dependence, Proc. of the American Control Conference, (2015) Chicago, IL, USA, pp. 831-837. (pdf) (link)
  33. R. Duijkers, R. Tóth, D. Piga and V. Laurain: Shrinking Complexity of Scheduling Dependencies in LS-SVM Based LPV System Identification, Invited paper, Proc. of the 53rd IEEE Conference on Decision and Control, (2014) Los Angeles, CA, USA, pp. 2561-2566. (pdf) (link)
  34. A. Golabi, N. Meskin, R. Tóth and M. Mohammadpour: A Bayesian Approach for Estimation of LPV Linear-Regression Models, Invited paper, Proc of the 53rd IEEE Conference on Decision and Control, (2014) Los Angeles, CA, USA, pp. 2555-2560. (pdf) (link)
  35. Abbas, H.S., R. Tóth, M. Petreczky, N. Meskin and J. Mohammadpour: Embedding of Nonlinear Systems in a Linear Parameter-Varying Representation, Proc. of the 19th IFAC World Congress, (2014) Cape Town, South Africa, pp. 6907-6913. (pdf) (link)
  36. Lataire, J., D. Piga and R. Tóth: Frequency-domain least-squares support vector machines to deal with correlated errors when identifying linear time-varying systems, Proc. of the 19th IFAC World Congress, (2014) Cape Town, South Africa, pp. 10024-10029. (pdf) (link)
  37. Rizvi, S. Z., J. Mohammadpour, R. Tóth and N. Meskin: Parameter Set-mapping using Kernel-based PCA for Linear Parameter Varying Systems, Proc. of the 13th European Control Conference, (2014) Strasbourg, France, pp. 2744-2749. (pdf) (link)
  38. Abbasi, F., J. Mohammadpour, R. Tóth and N. Meskin: A support vector machine-based method for LPV-ARX identification with noisy scheduling parameters. Proc. of the 13th European Control Conference, (2014) Strasbourg, France, pp. 370-375. (pdf) (link)
  39. Wollnack, S., H. S. Abbas, H. Werner and R. Tóth: Fixed-Structure LPV Controller Synthesis based on Implicit Input Output Representations, Proc. of the 52nd IEEE Conference on Decision and Control, (2013) Florence, Italy, pp. 2103-2108. (pdf) (link)
  40. Piga, D. and R. Tóth: LPV model order selection in an LS-SVM setting, Invited paper, Proc. of the 52nd IEEE Conference on Decision and Control, (2013) Florence, Italy, pp. 4128-4133. (pdf) (link)
  41. Formentin, S., D. Piga, R. Tóth and S. M. Savaresi: Direct data-driven control of linear parameter-varying systems, Invited paper, Proc. of the 52nd IEEE Conference on Decision and Control, (2013) Florence, Italy, pp. 4110-4115. (pdf) (link)
  42. Bachnas, A. A., R. Tóth, A. Mesbah and J. Ludlage:  Perspectives of data-driven LPV modeling of high-purity distillation columns, Invited paper, Proc. of the European Control Conference, (2013) Zurich, Switzerland, pp. 3776-3783. (pdf) (link)
  43. Tóth, R., H. Hjalmarsson and C. R. Rojas: Order and Structural Dependence Selection of LPV-ARX Models Revisited, Invited paper, Proc. of the 51st IEEE Conference on Decision and Control, (2012) Maui, Hawaii, USA, pp. 6271-6276. (pdf) (link)
  44. Siraj, M. M., R. Tóth, S. Weiland: Joint order and dependency reduction for LPV state-space models, Invited paper, Proc. of the 51st IEEE Conference on Decision and Control, (2012) Maui, Hawaii, USA, pp. 6291-6296. (pdf) (link)
  45. Cerone, V., D. Piga, D. Regruto and R. Tóth: Fixed order LPV controllers design for LPV models in input-output form, Invited paper, Proc. of the 51st IEEE Conference on Decision and Control, (2012) Maui, Hawaii, USA, pp. 6297-6302. (pdf) (link)
  46. Tóth, R., H. Hjalmarsson and C. R. Rojas: Sparse estimation of polynomial dynamical models, Invited paper, Proc. of the 16th IFAC Symposium on System Identification, (2012) Brussels, Belgium, pp. 983-988 . (pdf) (link)
  47. Laurain, V., R. Tóth, W-X. Zheng and M. Gilson: Nonparametric identification of LPV models under general noise conditions: an LS-SVM based approach, Invited paper, Proc. of the 16th IFAC Symposium on System Identification, (2012) Brussels, Belgium, pp. 1761-1766. (pdf) (link)
  48. Cerone, V., D. Piga, D. Regruto and R. Tóth: Input-output LPV model identification with guaranteed quadratic stability, Invited paper, Proc. of the 16th IFAC Symposium on System Identification, (2012) Brussels, Belgium, pp. 1767-1772. (pdf) (link)
  49. Cerone, V., D. Piga, D. Regruto and R. Tóth: Minimal LPV state-space realization driven set-membership identification. Proc. of the American Control Conf., (2012) Montréal, Canada, pp. 3421-3426. (pdf) (link)
  50. Dankers, A. G., R. Tóth, P. S. C. Heuberger, X. Bombois and P. M. J. Van den Hof: Informative data and identifiability in LPV-ARX prediction error identification, Proc. of the 50th IEEE Conference on Decision and Control, (2011) Orlando, Florida, USA, pp. 799-804. (pdf) (link)
  51. Laurain, V., W-X. Zheng and R. Tóth: Introducing instrumental variables in the LS-SVM based identification framework, Proc. of the 50th IEEE Conference on Decision and Control, (2011) Orlando, Florida, USA, pp. 3198-3203. (pdf) (link)
  52. Tóth, R., V. Laurain, W-X. Zheng and K. Poolla: Model structure learning: A support vector machine approach for LPV linear-regression models, Proc. of the 50th IEEE Conference on Decision and Control, (2011) Orlando, Florida, USA, pp. 3192-3197. (pdf) (errata) (link)
  53. Tóth, R., B. M. Sanandaji, K. Poolla and T. L. Vincent: Compressive system identification in the linear time-invariant framework, Proc. of the 50th IEEE Conference on Decision and Control, (2011) Orlando, Florida, USA, pp. 783-790. (pdf) (link)
  54. Sanandaji, B. M., T. L. Vincent, M. B. Wakin, R. Tóth and K. Poolla: Compressive system identification of LTI and LTV ARX models: The limited data set case, Proc. of the 50th IEEE Conference on Decision and Control, (2011) Orlando, Florida, USA, 791-798. (pdf) (link)
  55. Tóth, R., V. Laurain, M. Gilson and H. Garnier: On the closed loop identification of LPV models using instrumental variables. Proc. of the 18th IFAC World Congress, (2011), Milano, Italy, pp. 7773-7778 (pdf) (link)
  56. Kulcsár, B. and R. Tóth: On the similarity state transformation for linear parameter-varying systems. Proc. of the 18th IFAC World Congress, (2011), Milano, Italy, pp. 4155-4160. (pdf) (link)
  57. Tóth, R., M. van de Wal, P. S. C. Heuberger and P. M. J. Van den Hof: LPV Identification of High Performance Positioning Devices. Invited paper, Proc. of the American Control Conf., (2011) San Francisco, California, USA, pp. 151-158. (pdf) (link)
  58. Laurain, V., M. Gilson, R. Tóth and H. Garnier: Direct identification of continuous-time LPV models. Invited paper, Proc. of the American Control Conf., (2011) San Francisco, California, USA, pp. 159-164. (pdf) (link)
  59. Tóth, R., P. M. J. Van den Hof, J. H. A. Ludlage and P. S. C. Heuberger: Identification of nonlinear process models in an LPV framework. Proc. of the 9th International Symp. on Dynamics and Control of Process Systems, (2010) Leuven, Belgium, pp. 869-874. (pdf) (link)
  60. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: A prediction-error identification framework for linear parameter-varying systems. Invited paper, Proc. of the 19th International Symposium on Mathematical Theory of Networks and Systems, (2010) Budapest, Hungary, pp. 1351-1352. (pdf)
  61. Abbas H., R. Tóth, and H. Werner, State-space realization of LPV input-output models: practical methods for the user, Invited paper, Proc. of the American Control Conf., (2010) Baltimore, Maryland, USA, pp. 3883-3888. (pdf) (link)
  62. Laurain, V., M. Gilson, R. Tóth, and H. Garnier, Identification of LPV Output-Error and Box-Jenkins Models via Optimal Refined Instrumental Variable Methods, Invited paper, Proc. of the American Control Conf., (2010) Baltimore, Maryland, USA, pp. 3865-3870. (pdf) (link)
  63. Tóth, R., M. Lovera, P. S. C. Heuberger and P. M. J. Van den Hof: Discretization of Linear Fractional Representations of LPV systems, Proc. of the 48th IEEE Conference on Decision and Control, (2009) Shanghai, China, pp. 7424-7429. (pdf) (link)
  64. Tóth, R., C. Lyzell, M. Enqvist, P. S. C. Heuberger and P. M. J. Van den Hof: Order and Structural Dependence Selection of LPV-ARX Models Using a Nonnegative Garrote Approach, Proc. of the 48th IEEE Conference on Decision and Control, (2009) Shanghai, China, pp. 7406-7411. (pdf) (link)
  65. Tóth, R., Jan C. Willems, P. S. C. Heuberger and P. M. J. Van den Hof: A behavioral approach to LPV systems, Proc. of the European Control Conference, (2009) Budapest, Hungary, pp. 2015-2020. (pdf) (link)
  66. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: An LPV identification Framework Based on Orthonormal Basis Functions. Proc. of the 15th IFAC Symposium on System Identification, (2009) St. Malo, France, pp. 1328-1333. (pdf) (link)
  67. Khalate, A. A., X. Bombois, R. Tóth and R. Babuška: Optimal experimental design for LPV identification using a local approach. Proc. of the 15th IFAC Symposium on System Identification, (2009) St. Malo, France, pp. 162-167. (pdf) (link)
  68. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: Flexible model structures for LPV identification with static scheduling dependency, Invited paper, Proc. of the 47th IEEE Conference on Decision and Control, (2008) Cancun, Mexico, pp. 4522-4527. (pdf) (link)
  69. Tóth, R., F. Felici, P. S. C. Heuberger and P. M. J. Van den Hof: Crucial aspects of zero-order hold LPV state-space system discretization, Proc. of the 17th IFAC World Congress, (2008) Seoul, Korea, pp. 4952-4957. (pdf) (link)
  70. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: LPV system identification with globally fixed orthonormal basis functions, Proc. of the 46th IEEE Conference on Decision and Control, (2007) New Orleans, USA, pp. 3646-3653. (pdf) (link)
  71. Tóth, R., F. Felici, P. S. C. Heuberger and P. M. J. Van den Hof: Discrete time LPV I/O and state-space representations, differences of behavior and pitfalls of interpolation, Proc. of the European Control Conference, (2007) Kos, Greece, pp. 5418-5425.  (pdf) (errata) (link)
  72. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: Orthonormal basis selection for LPV system identification, the Fuzzy-Kolmogorov c-Max approach, Proc. of the 45th IEEE Conf. on Decision and Control, (2006) San Diego, USA, pp. 2529-2534. (pdf) (link)
  73. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: Optimal pole selection for LPV system identification with OBFs, a clustering approach, Proc. of the 14th IFAC Symposium on System Identification, (2006) Newcastle, Australia, pp. 356-361. (pdf) (link)
  74. Tóth, R. and D. Fodor: Speed Sensorless mixed sensitivity linear parameter variant H_inf control of the induction motor, Proc. of the 43rd IEEE Conference on Decision and Control, (2004) Nassau, The Bahamas, pp. 4435-4440. (pdf) (link)

Submitted Conference Papers (0)

Plenary Talks (1)

R. Tóth: Finding the golden mean in data-driven modeling. Plenary talk at the 16th IFAC Symposium on System Identification, (2012) Brussels. (pptx)


Abstracts (23)

  1. Hanema, J., R. Tóth, M. Lazar: Tube-based anticipative linear parameter-varying MPC: application to non-linear systems, Proc. of the 36th Benelux Meeting, (2017) Spa, Belgium, pp. 115.
  2. Proimadis, I., and R. Tóth: Modelling of a nanometer-accurate planar actuation system, Proc. of the 36th Benelux Meeting, (2017) Spa, Belgium, pp. 92.
  3. Darwish, M.A.H.,  J. Lataire, R. Tóth and P. M. J. Van den Hof: Bayesian Frequency Domain Identification of LTI Systems with OBFs Kernels, Proc. of the 36th Benelux Meeting, (2017) Spa, Belgium, pp. 18.
  4. Proimadis, I., and R. Tóth: Nanometer-accurate planar actuation system (NAPAS), Proc. of the 36th Benelux Meeting, (2016) Soesterberg, The Netherlands, pp. 156.
  5. Bachnas, A.A., S. Weiland and R. Tóth: Characterization of the tracking error for OBF based MPC, Proc. of the 36th Benelux Meeting, (2016) Soesterberg, The Netherlands, pp. 119.
  6. Khandelwal, D., and R. Tóth: Data-driven modelling using symbolic regression, Proc. of the 36th Benelux Meeting, (2016) Soesterberg, The Netherlands, pp. 111.
  7. Darwish, M.A.H., S. Chitraganti, T.B. Schön, R. Tóth and P.M.J. van den Hof: Maximum likelihood estimation of LPV-SS models: A Sequential Monte-Carlo approach, Proc. of the 36th Benelux Meeting, (2016) Soesterberg, The Netherlands, pp. 81.
  8. Cox, P.B., R. Tóth and P.M.J. van den Hof:  On the connection between different noise structures for LPV-SS models, Proc. of the 35th Benelux Meeting, (2016) Soesterberg, The Netherlands, pp. 78.
  9. Hanema, J., R. Tóth, M. Lazar and S. Weiland: Towards anticipative LPV tube model predictive control, Proc. of the 35th Benelux Meeting, (2016) Soesterberg, The Netherlands, pp. 67.
  10. Cox, P., R. Tóth and P.M.J. Van den Hof:  Estimation of LPV-SS Models with Static Dependency, Proc. of the 34th Benelux Meeting, (2015) Lommel, Belgium.
  11. Darwish M.A.H., R. Tóth and P.M.J. Van den Hof:  Selecting Shaping Kernels in Bayesian Identification of LTI Systems: An Orthonormal Basis Functions Approach, Proc. of the 34th Benelux Meeting, (2015) Lommel, Belgium.
  12. Hanema J., R. Tóth M. Lazar and S. Weiland:  Anticipative linear parameter-varying model predictive control, Proc. of the 34th Benelux Meeting, (2015) Lommel, Belgium.
  13. Bachnas, A.A., S.Weiland and R. Tóth: Data driven MPC based on OBF model structures, Proc. of the 34th Benelux Meeting, (2015) Lommel, Belgium.
  14. Cox, P., R. Tóth and P.M.J. Van den Hof: Identification of Linear Parameter Varying Input-Output Models with Noisy Measurements of the Scheduling Variable, Proc. of the 33rd Benelux Meeting, (2014) Heijden, The Netherlands, pp. 75.
  15. Darwish, M. A. H., R. Tóth and P.M.J. Van den Hof: Learning Models and Controllers from Data, Proc. of the 33rd Benelux Meeting, (2014) Heijden, The Netherlands, pp. 68.
  16. Bachnas, A. A., S. Weiland and R. Tóth: Uncertainty reduction techniques via orthonormal basis function based control synthesis, Proc. of the 33rd Benelux Meeting, (2014) Heijden, The Netherlands, pp. 90.
  17. Tóth, R., V. Laurain and D. Piga: An Instrumental Least Squares Support Vector Machine for System Identification, Workshop on Machine Learning for System Identification, (2013) Atlanta, Georgia, USA.
  18. Siraj, M.M. and R. Tóth: On The Problem of Model Reduction of LPV Systems, Proc. of the 31st Benelux Meeting, (2012) Heijderbos, The Netherlands, pp. 146.
  19. Dankers, A. G., R. Tóth, P. S. C. Heuberger and P. M. J. Van den Hof: Informativity of Data Sets for LPV Prediction-Error Identification, Proc. of the 30th Benelux Meeting, (2011) Lommel, Belgium, pp. 70.
  20. Tóth, R., J.C. Willems, P. S. C. Heuberger and P. M. J. Van den Hof: Extension of the behavioral approach to linear parameter-varying systems, Proc. of the 28th Benelux Meeting, (2009) Spa, Belgium, pp. 131.
  21. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: (In)equivalence of discrete time LPV state-space and input/output representations, Proc. of the 26th Benelux Meeting, (2007) Lommel, Belgium, pp. 34.
  22. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: Robust and optimal selection of OBFs based model structures, Proc. of the 25th Benelux Meeting, (2006) Heeze, The Netherlands, pp. 27.
  23. Tóth, R., P. S. C. Heuberger and P. M. J. Van den Hof: Identification of LPV systems using orthonormal basis functions, Proc. of the 24th Benelux Meeting, (2005) Houffalize, Belgium, pp. 70.

Technical Reports (10)

  1. Darwish, M. A. H., P. B. Cox, I. Proimadis, G. Pillonetto and R. Tóth: Prediction-Error Identification of LPV Systems: A Nonparametric Gaussian Regression Approach, TUE-CS-2017-001, 2016. (pdf)
  2. Cox, P. B. and R. Tóth: On the Connection Between Different Noise Structures for LPV-SS Models, Eindhoven University of Technology, TUE-CS-2016-003, 2016. (pdf)
  3. R. Tóth: IO realization of an LPV-SS form with static dependency, TUE–CS-2015-001, 2015. (pdf)
  4. Wollnack, S, A. S. Hossam, Herbert Werner, and R. Tóth: Using Implicit IO Representations for Stability Analysis and LPV-IO Controller Synthesis. Eindhoven University of Technology, TUE–CS-2014-003, 2014. (pdf)
  5. Laurain, V., R. Tóth, D. Piga: Instrumental Variables Based Least Squares Support Vector Machine for Identification of Nonlinear Systems, Eindhoven University of Technology, TUE–CS-2013-005, 2013. (pdf)
  6. Formentin, S., D. Piga, R. Tóth, and S. Savaresi. LPV control system design from data, Eindhoven University of Technology, TUE–CS-2013-004, 2013. (pdf)
  7. R. Tóth: Maximum LPV-SS realization in a static form, Eindhoven University of Technology, TUE–CS-2013-003, 2013. (pdf)
  8. Piga, D. and R. Tóth: Data-driven LPV modeling of continuous pulp digesters, Eindhoven University of Technology, TUE–CS-2013-002, 2013. (pdf)
  9. Laurain, V., R. Tóth, D. Piga: An Instrumental Least Squares Support Vector Machine for Nonlinear System Identification: enforcing zero-centering constraints, Eindhoven University of Technology, TUE–CS-2013-001, 2013. (pdf)
  10. Tóth, R., M. Lovera, P. S. C. Heuberger, M. Corno and P. M. J. Van den Hof: On the Discretization of Linear Fractional Representations of LPV Systems: Detailed Derivation of the Formulas, Tech. Report, Delft University of Technology, R-11-037, 2011. (pdf)

Lecture notes (2)

  1. Tóth, R. and A. Balogh: Collection of problems and solutions for electrical circuits, Lecture Notes in Electrical Engineering, in Hungarian, Pannon University, 2002.
  2. Fodor, D. and R. Tóth: Digital Signal Processing, Lecture Notes in Electrical Engineering, in Hungarian, Pannon University, 2002.

Theses (3)

  1. Tóth, R.: Modeling and Identification of Linear Parameter-Varying Systems, an Orthonormal Basis Function Approach, Phd. Thesis, Delft University of Technology, 2008.
  2. Tóth, R.: Speed Sensorless Mixed Sensitivity H_inf Control of The Induction Motor, Msc. Thesis, Pannon University, 2004. (pdf)
  3. Tóth, R.: Implementation of a Speed Sensorless Induction Motor Control on TMS320F243, Bsc. Thesis, Pannon University, 2004. (pdf)