61 citations · 64 across the 5 of their papers we have counts for
5 papers
Gaussian behaviors and stochastic data-driven control
András Sasfi, Alberto Padoan, Ivan Markovsky +1
We propose a stochastic behavioral modeling framework, termed Gaussian behaviors, which augments a deterministic linear time-invariant (LTI) behavior with a Gaussian noise componen…
Soft projections for robust data-driven control
András Sasfi, Jaap Eising, Florian Dörfler
We consider data-based predictive control based on behavioral systems theory. In the linear setting this means that a system is described as a subspace of trajectories, and predict…
Gaussian behaviors: representations and data-driven control
András Sasfi, Ivan Markovsky, Alberto Padoan +1
We propose a modeling framework for stochastic systems, termed Gaussian behaviors, that describes finite-length trajectories of a system as a Gaussian process. The proposed model n…
GREAT: Grassmannian REcursive Algorithm for Tracking & Online System Identification
András Sasfi, Alberto Padoan, Ivan Markovsky +1
This paper introduces an online approach for identifying time-varying subspaces defined by linear dynamical systems. The approach of representing linear systems by non-parametric s…
Robust adaptive MPC using control contraction metrics
András Sasfi, Melanie N. Zeilinger, Johannes Köhler
We present a robust adaptive model predictive control (MPC) framework for nonlinear continuous-time systems with bounded parametric uncertainty and additive disturbance. We utilize…