24 citations · 59 across the 11 of their papers we have counts for
5 papers · 1 filter
On Recurrent Neural Networks for learning-based control: recent results and ideas for future developments
Fabio Bonassi, Marcello Farina, Jing Xie +1
This paper aims to discuss and analyze the potentialities of Recurrent Neural Networks (RNN) in control design applications. The main families of RNN are considered, namely Neural…
Robust Tube-based Model Predictive Control with Koopman Operators--Extended Version
Xinglong Zhang, Wei Pan, Riccardo Scattolini +2
Koopman operators are of infinite dimension and capture the characteristics of nonlinear dynamics in a lifted global linear manner. The finite data-driven approximation of Koopman…
Recurrent Neural Network-based Internal Model Control design for stable nonlinear systems
Fabio Bonassi, Riccardo Scattolini
Owing to their superior modeling capabilities, gated Recurrent Neural Networks, such as Gated Recurrent Units (GRUs) and Long Short-Term Memory networks (LSTMs), have become popula…
Nonlinear MPC for Offset-Free Tracking of systems learned by GRU Neural Networks
Fabio Bonassi, C. F. Oliveira da Silva, Riccardo Scattolini
The use of Recurrent Neural Networks (RNNs) for system identification has recently gathered increasing attention, thanks to their black-box modeling capabilities.Albeit RNNs have b…
Robust multi-rate predictive control using multi-step prediction models learned from data
Enrico Terzi, Lorenzo Fagiano, Marcello Farina +1
This note extends a recently proposed algorithm for model identification and robust MPC of asymptotically stable, linear time-invariant systems subject to process and measurement d…