95 citations · 364 across the 28 of their papers we have counts for
5 papers · 1 filter
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…
Robust offset-free nonlinear model predictive control for systems learned by neural nonlinear autoregressive exogenous models
Jing Xie, Fabio Bonassi, Marcello Farina +1
This paper presents a robust Model Predictive Control (MPC) scheme that provides offset-free setpoint tracking for systems described by Neural Nonlinear AutoRegressive eXogenous (N…
Towards lifelong learning of Recurrent Neural Networks for control design
Fabio Bonassi, Jing Xie, Marcello Farina +1
This paper proposes a method for lifelong learning of Recurrent Neural Networks, such as NNARX, ESN, LSTM, and GRU, to be used as plant models in control system synthesis. The prob…
An Offset-Free Nonlinear MPC scheme for systems learned by Neural NARX models
Fabio Bonassi, Jing Xie, Marcello Farina +1
This paper deals with the design of nonlinear MPC controllers that provide offset-free setpoint tracking for models described by Neural Nonlinear AutoRegressive eXogenous (NNARX) n…
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…