28 papers
Robust stability of event-triggered nonlinear moving horizon estimation
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller +1
In this work, we propose an event-triggered moving horizon estimation (ET-MHE) scheme for the remote state estimation of general nonlinear systems. In the presented method, wheneve…
Sample-based detectability and moving horizon state estimation of continuous-time systems
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
In this paper we propose a detectability condition for nonlinear continuous-time systems with irregular/infrequent output measurements, namely a sample-based version of incremental…
Robust and efficient data-driven predictive control
Mohammad Alsalti, Manuel Barkey, Victor G. Lopez +1
We propose a robust and efficient data-driven predictive control (eDDPC) scheme which is more sample efficient (requires less offline data) compared to existing schemes, and is als…
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…
Local Observability and Moving Horizon Estimation-based Training of Feedforward Neural Networks
Yi Yang, Victor G. Lopez, Matthias A. Müller
In this paper, we propose a moving horizon estimation (MHE)-based training method for feedforward neural networks (FNNs) with rectified linear unit (ReLU) activation functions to d…
Beyond Shrinkage: Foundations of Data-Driven Control for Piecewise Affine Systems
Gianluca Giacomelli, Victor G. Lopez, Simone Formentin +2
Data-enabled predictive control (DeePC) has recently attracted attention as a promising approach for controlling systems directly from raw data, without requiring an explicit ident…