59 citations · 160 across the 12 of their papers we have counts for
13 papers
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…
Robust Stability of Gaussian Process Based Moving Horizon Estimation
Tobias M. Wolff, Victor G. Lopez, Matthias A. Müller
In this paper, we introduce a Gaussian process based moving horizon estimation (MHE) framework. The scheme is based on offline collected data and offline hyperparameter optimizatio…
An Efficient Off-Policy Reinforcement Learning Algorithm for the Continuous-Time LQR Problem
Victor G. Lopez, Matthias A. Müller
In this paper, an off-policy reinforcement learning algorithm is designed to solve the continuous-time LQR problem using only input-state data measured from the system. Different f…
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…
Data-driven Nonlinear Predictive Control for Feedback Linearizable Systems
Mohammad Alsalti, Victor G. Lopez, Julian Berberich +2
We present a data-driven nonlinear predictive control approach for the class of discrete-time multi-input multi-output feedback linearizable nonlinear systems. The scheme uses a no…
Robust Data-Driven Moving Horizon Estimation for Linear Discrete-Time Systems
Tobias M. Wolff, Victor G. Lopez, Matthias A. Müller
In this paper, a robust data-driven moving horizon estimation (MHE) scheme for linear time-invariant discrete-time systems is introduced. The scheme solely relies on offline collec…
Sample-based observability of linear discrete-time systems
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
In this work, sample-based observability of linear discrete-time systems is studied. That is, we consider the case where the system output measurements are not available at every t…
Practical exponential stability of a robust data-driven nonlinear predictive control scheme
Mohammad Alsalti, Victor G. Lopez, Julian Berberich +2
We provide theoretical guarantees for recursive feasibility and practical exponential stability of the closed-loop system of a feedback linearizable nonlinear system when controlle…
Data-based Control of Feedback Linearizable Systems
Mohammad Alsalti, Victor G. Lopez, Julian Berberich +2
We present an extension of Willems' Fundamental Lemma to the class of multi-input multi-output discrete-time feedback linearizable nonlinear systems, thus providing a data-based re…
On a Continuous-Time Version of Willems' Lemma
Victor G. Lopez, Matthias A. Müller
In this paper, a method to represent every input-output trajectory of a continuous-time linear system in terms of previously collected data is presented. This corresponds to a cont…
Data-Based Moving Horizon Estimation for Linear Discrete-Time Systems
Tobias M. Wolff, Victor G. Lopez, Matthias A. Müller
This paper introduces a data-based moving horizon estimation (MHE) scheme for linear time-invariant discrete-time systems. The scheme solely relies on collected data without employ…
Efficient Off-Policy Q-Learning for Data-Based Discrete-Time LQR Problems
Victor G. Lopez, Mohammad Alsalti, Matthias A. Müller
This paper introduces and analyzes an improved Q-learning algorithm for discrete-time linear time-invariant systems. The proposed method does not require any knowledge of the syste…
Data-Based System Analysis and Control of Flat Nonlinear Systems
Mohammad Alsalti, Julian Berberich, Victor G. Lopez +2
Willems et al. showed that all input-output trajectories of a discrete-time linear time-invariant system can be obtained using linear combinations of time shifts of a single, persi…