Publications
Journal papers
[J7] M. Alsalti, V. G. Lopez and M. A. Müller, “Notes on data-driven output-feedback control of linear MIMO systems“, submitted to IEEE Transactions on Automatic Control, 2023, pre-print available: arXiv:2311.17484.
[J6] M. Alsalti, I. Markovsky, V. G. Lopez and M. A. Müller, “Data-based system representations from irregularly measured data," submitted to IEEE Transactions on Automatic Control, 2023, pre-print available: arXiv:2307.11589.
[J5] I. Markovsky, M. Alsalti, V. G. Lopez and M. A. Müller, “Identification from data with periodically missing output samples," submitted to Automatica, 2023, pre-print available: 10.15488/15821.
[J4] M. Alsalti, V. G. Lopez and M. A. Müller, “On the design of persistently exciting inputs for data-driven control of linear and nonlinear systems“, IEEE Control Systems Letters, 2023, doi: 10.1109/LCSYS.2023.3287133, pre-print available: arXiv: 2303.08707.
[J3] M. Alsalti, V. G. Lopez, J. Berberich, F. Allgöwer and M. A. Müller, "Data-Based Control of Feedback Linearizable Systems," IEEE Transactions on Automatic Control, 2023, doi:10.1109/TAC.2023.3249289, pre-print available: arXiv: 2204.01148.
[J2] V. G. Lopez, M. Alsalti, and M. A. Müller, “Efficient off-policy Q-learning for data-based discrete-time LQR problems,” IEEE Transactions on Automatic Control, 2023, doi:10.1109/TAC.2023.3235967, pre-print available: arXiv: 2105.07761.
[J1] M. Alsalti, A. Tivay, X. Jin, G. C. Kramer, and J. Hahn, "Design and In Silico Evaluation of a Closed-Loop Hemorrhage Resuscitation Algorithm With Blood Pressure as Controlled Variable." ASME Dynamic Systems, Measurement, and Control, February 2022; 144(2): 021001, doi: 10.1115/1.4052312 .
Conference papers
[C4] M. Alsalti, V. G. Lopez and M. A. Müller, "An efficient data-based Q-learning algorithm for optimal output feedback control of linear systems" accepted for the 6th L4DC conference, 2024, pre-print and m-files are available on doi:10.25835/zmlriehg or arXiv:2312.03451.
[C3] M. Alsalti, M. Barkey, V. G. Lopez and M. A. Müller, "Sample- and computationally efficient data-driven predictive control," accepted for the 22nd European Control Conference, 2024, pre-print available: arXiv: 2309.11238.
[C2] M. Alsalti, V. G. Lopez, J. Berberich, F. Allgöwer and M. A. Müller, ”Data-driven Nonlinear Predictive Control for Feedback Linearizable Systems”, 22nd IFAC World Congress 2023, doi:10.1016/j.ifacol.2023.10.1636, pre-print available: arXiv: 2211.06339.
[C1] M. Alsalti, J. Berberich, V. G. Lopez, F. Allgöwer and M. A. Müller, "Data-Based System Analysis and Control of Flat Nonlinear Systems," 60th IEEE Conference on Decision and Control (CDC), 2021, pp. 1484-1489, doi: 10.1109/CDC45484.2021.9683327 .
Reports and abstracts
M. Alsalti, V. G. Lopez, J. Berberich, F. Allgöwer and M. A. Müller, "Practical exponential stability of a robust data-driven nonlinear predictive control scheme," supplementary technical report to 22nd IFAC WC paper, available: arXiv:2204.01150, 2022.