59 citations · 130 across the 11 of their papers we have counts for
5 papers · 1 filter
An efficient data-based off-policy Q-learning algorithm for optimal output feedback control of linear systems
Mohammad Alsalti, Victor G. Lopez, Matthias A. Müller
In this paper, we present a Q-learning algorithm to solve the optimal output regulation problem for discrete-time LTI systems. This off-policy algorithm only relies on using persis…
Notes on data-driven output-feedback control of linear MIMO systems
Mohammad Alsalti, Victor G. Lopez, Matthias A. Müller
Recent works have approached the data-driven design of dynamic output-feedback controllers for discrete-time LTI systems by constructing non-minimal state vectors composed of past…
Sample- and computationally efficient data-driven predictive control
Mohammad Alsalti, Manuel Barkey, Victor G. Lopez +1
Recently proposed data-driven predictive control schemes for LTI systems use non-parametric representations based on the image of a Hankel matrix of previously collected, persisten…
Data-based system representations from irregularly measured data
Mohammad Alsalti, Ivan Markovsky, Victor G. Lopez +1
Non-parametric representations of dynamical systems based on the image of a Hankel matrix of data are extensively used for data-driven control. However, if samples of data are miss…
On the design of persistently exciting inputs for data-driven control of linear and nonlinear systems
Mohammad Alsalti, Victor G. Lopez, Matthias A. Müller
In the context of data-driven control, persistence of excitation (PE) of an input sequence is defined in terms of a rank condition on the Hankel matrix of the input data. For nonli…