75 citations · 309 across the 47 of their papers we have counts for
10 papers · 1 filter
Sample-based nonlinear detectability for discrete-time systems
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
This paper introduces two sample-based formulations of incremental input/output-to-state stability (i-IOSS), a suitable detectability notion for general nonlinear systems. In this…
Nonlinear moving horizon estimation for robust state and parameter estimation -- extended version
Julian D. Schiller, Matthias A. Müller
We propose a moving horizon estimation scheme to estimate the states and the unknown constant parameters of general nonlinear uncertain discrete-time systems. The proposed framewor…
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…
Analysis and design of model predictive control frameworks for dynamic operation -- An overview
Johannes Köhler, Matthas A. Müller, Frank Allgöwer
This article provides an overview of model predictive control (MPC) frameworks for dynamic operation of nonlinear constrained systems. Dynamic operation is often an integral part o…
Robust stability of moving horizon estimation for continuous-time systems
Julian D. Schiller, Matthias A. Müller
We consider a moving horizon estimation (MHE) scheme involving a discounted least squares objective for general nonlinear continuous-time systems. Provided that the system is detec…
Distributed Model Predictive Control for Periodic Cooperation of Multi-Agent Systems
Matthias Köhler, Matthias A. Müller, Frank Allgöwer
We consider multi-agent systems with heterogeneous, nonlinear agents subject to individual constraints that want to achieve a periodic, dynamic cooperative control goal which can b…
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…
Transient Performance of MPC for Tracking
Matthias Köhler, Lisa Krügel, Lars Grüne +2
We analyse the closed-loop performance of a model predictive control (MPC) for tracking formulation with artificial references. It has been shown that such a scheme guarantees clos…
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…