Publikationen

Alsalti, M.; Barkey, M.; Lopez, V. G. & Müller, M. A. (2023): Sample- and computationally efficient data-driven predictive control,  submitted
arXiv: 2309.11238

Alsalti, M.; Lopez, V. G. & Müller, M. A. (2023): On the design of persistently exciting inputs for data-driven control of linear and nonlinear systems,  IEEE Control Systems Letters, vol. 7, pp. 2629 - 2634
DOI: 10.1109/LCSYS.2023.3287133
arXiv: 2303.08707

Alsalti, M.; Lopez, V. G. & Müller, M. A. (2023): Notes on data-driven output-feedback control of linear MIMO systems,  submitted
arXiv: 2311.17484

Alsalti, M.; Lopez, V. G. & Müller, M. A. (2023): An efficient data-based off-policy Q-learning algorithm for optimal output feedback control of linear systems,  submitted
arXiv: 2312.03451

Alsalti, M.; Lopez, V. G; Berberich, J.; Allgöwer, F. & Müller, M. A. (2023): Data-Based Control of Feedback Linearizable Systems,  IEEE Transactions on Automatic Control (Early Access)
DOI: 10.1109/TAC.2023.3249289
arXiv: 2204.01148

Alsalti, M.; Markovsky, I.; Lopez, V. G. & Müller, M. A. (2023): Data-based system representations from irregularly measured data,  submitted
arXiv: 2307.11589

Krauss, I.; Lopez, V. G. & Müller, M. A. (2023): Sample-based nonlinear detectability for discrete-time systems,  submitted
arXiv: 2312.13658

Lopez, V. G.; Alsalti, M. & Müller, M. A. (2023): Efficient Off-Policy Q-Learning for Data-Based Discrete-Time LQR Problems,  IEEE Transactions on Automatic Control, pp. 1-12
DOI: 10.1109/TAC.2023.3235967

Markovsky, I.; Alsalti, M. ; Lopez, V. G. & Müller, M. A. (2023): Identification from data with periodically missing output samples,  submitted
DOI: 10.15488/15821

Wolff, T.; Lopez, V. G. & Müller, M. A. (2022): Robust Data-Driven Moving Horizon Estimation for Linear Discrete-Time Systems,  submitted
arXiv: 2210.09017

Alsalti, M.; Lopez, V. G.; Berberich, J.; Allgöwer, F. & Müller, M. A. (2023): Data-driven nonlinear predictive control for feedback linearizable systems,  22nd IFAC World Congress: Yokohama, Japan, July 9-14, 2023. IFAC-PapersOnLine, Vol. 56, Issue 2, pp. 617-624
DOI: 10.1016/j.ifacol.2023.10.1636
arXiv: 2211.06339

Lopez, V. G. & Müller, M. A. (2023): An efficient off-policy reinforcement learning algorithm for the continuous-time LQR problem,  Accepted for IEEE 62nd Conference on Decision and Control (CDC)
arXiv: 2303.17819

Wolff, T. M. & Lopez, V. G. & Müller, M. A. (2023): Robust Stability of Gaussian Process Based Moving Horizon Estimation,  2023 IEEE 62nd Conference on Decision and Control (CDC), pp. 4087-4093
DOI: 10.1109/CDC49753.2023.10383304
arXiv: 2304.06530

Krauss, I.; Lopez, V. G. & Müller, M. A. (2022): Sample-based observability of linear discrete-time systems,  2022 IEEE 61st Conference on Decision and Control (CDC)
DOI: 10.1109/CDC51059.2022.9993267

Lopez, V. G. & Müller, M. A. (2022): On a continuous-time version of Willems' lemma,  IEEE 61st Conference on Decision and Control (CDC), pp. 2759-2764
DOI: 10.1109/CDC51059.2022.9992347

Wolff, T. M.; Lopez, V. G. & Müller, M. A. (2022): Data-Based Moving Horizon Estimation for Linear Discrete-Time Systems,  2022 European Control Conference (ECC), pp. 1778-1783
DOI: 10.23919/ecc55457.2022.9838331
arXiv: 2111.04979

Alsalti, M.; Berberich, J.; Lopez, V. G.; Allgöwer, F. & Müller, M. A. (2021): Data-Based System Analysis and Control of Flat Nonlinear Systems,  60th IEEE Conference on Decision and Control (CDC), pp. 1484-1489
DOI: 10.1109/CDC45484.2021.9683327
arXiv: 2103.02892

Alsalti, M.; Berberich, J.;Lopez, V. G.; Allgöwer, F. & Müller, M. A. (2022): Practical exponential stability of a robust data-driven nonlinear predictive control scheme,  Supplementary material - technical report
arXiv: 2204.01150