2 citations · 3 across the 4 of their papers we have counts for
4 papers
Regional stability conditions for recurrent neural network-based control systems
Alessio La Bella, Marcello Farina, William D'Amico +1
In this paper we propose novel global and regional stability analysis conditions based on linear matrix inequalities for a general class of recurrent neural networks. These conditi…
An incremental input-to-state stability condition for a generic class of recurrent neural networks
William D'Amico, Alessio La Bella, Marcello Farina
This paper proposes a novel sufficient condition for the incremental input-to-state stability of a generic class of recurrent neural networks (RNNs). The established condition is c…
Virtual Reference Feedback Tuning for linear discrete-time systems with robust stability guarantees based on Set Membership
William D'Amico, Marcello Farina
In this paper we propose a novel methodology that allows to design, in a purely data-based fashion and for linear single-input and single-output systems, both robustly stable and p…
Advanced control based on Recurrent Neural Networks learned using Virtual Reference Feedback Tuning and application to an Electronic Throttle Body (with supplementary material)
William D'Amico, Marcello Farina, Giulio Panzani
In this paper the application of Virtual Reference Feedback Tuning (VRFT) for control of nonlinear systems with regulators defined by Echo State Networks (ESN) and Long Short Term…