1 citations · 1 across the 2 of their papers we have counts for
4 papers
Learning to control from expert demonstrations
Alimzhan Sultangazin, Luigi Pannocchi, Lucas Fraile +1
In this paper, we revisit the problem of learning a stabilizing controller from a finite number of demonstrations by an expert. By first focusing on feedback linearizable systems,…
Dirty derivatives for output feedback stabilization
Matteo Marchi, Lucas Fraile, Paulo Tabuada
Dirty derivatives are routinely used in industrial settings, particularly in the implementation of the derivative term in PID control, and are especially appealing due to their noi…
Data-driven Stabilization of SISO Feedback Linearizable Systems
Lucas Fraile, Matteo Marchi, Paulo Tabuada
In this paper we propose a methodology for stabilizing single-input single-output feedback linearizable systems when no system model is known and no prior data is available to iden…
A Note on Data-Driven Control for SISO Feedback Linearizable Systems Without Persistency of Excitation
Paulo Tabuada, Lucas Fraile
The paper [TF19] proposes a data-driven control technique for single-input single-output feedback linearizable systems with unknown control gain by relying on a persistency of exci…