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ORCIDRiccardo Scattolini
- > Home > Persons > Riccardo Scattolini
Publications
- 2024
[j70]Fabio Bonassi, Alessio La Bella
, Marcello Farina, Riccardo Scattolini:
Nonlinear MPC design for incrementally ISS systems with application to GRU networks. Autom. 159: 111381 (2024)- [i30]Jing Xie, Fabio Bonassi, Riccardo Scattolini:
Internal Model Control design for systems learned by Control Affine Neural Nonlinear Autoregressive Exogenous Models. CoRR abs/2402.05607 (2024) - 2023
- [c52]Fabio Bonassi, Alessio La Bella, Giulio Panzani, Marcello Farina, Riccardo Scattolini:
Deep Long-Short Term Memory networks: Stability properties and Experimental validation. ECC 2023: 1-6 - [i29]Fabio Bonassi, Alessio La Bella, Giulio Panzani, Marcello Farina, Riccardo Scattolini:
Deep Long-Short Term Memory networks: Stability properties and Experimental validation. CoRR abs/2304.02975 (2023) - [i28]Fabio Bonassi, Alessio La Bella, Marcello Farina, Riccardo Scattolini:
Nonlinear MPC design for incrementally ISS systems with application to GRU networks. CoRR abs/2309.16428 (2023) - 2022
- [j64]Fabio Bonassi, Riccardo Scattolini:
Recurrent Neural Network-based Internal Model Control design for stable nonlinear systems. Eur. J. Control 65: 100632 (2022) - [c49]Fabio Bonassi, Jing Xie, Marcello Farina, Riccardo Scattolini:
An Offset-Free Nonlinear MPC scheme for systems learned by Neural NARX models. CDC 2022: 2123-2128 - [c48]Fabio Bonassi, Jing Xie, Marcello Farina, Riccardo Scattolini:
Towards lifelong learning of Recurrent Neural Networks for control design. ECC 2022: 2018-2023 - [i26]Fabio Bonassi, Jing Xie, Marcello Farina, Riccardo Scattolini:
An Offset-Free Nonlinear MPC scheme for systems learned by Neural NARX models. CoRR abs/2203.16290 (2022) - [i25]Fabio Bonassi, Jing Xie, Marcello Farina, Riccardo Scattolini:
Towards lifelong learning of Recurrent Neural Networks for control design. CoRR abs/2208.03980 (2022) - [i24]Jing Xie, Fabio Bonassi, Marcello Farina, Riccardo Scattolini:
Robust offset-free nonlinear model predictive control for systems learned by neural nonlinear autoregressive exogenous models. CoRR abs/2210.06801 (2022) - 2021
- [j63]Fabio Bonassi, Marcello Farina, Riccardo Scattolini:
On the stability properties of Gated Recurrent Units neural networks. Syst. Control. Lett. 157: 105049 (2021) - [i22]Fabio Bonassi, Caio Fabio Oliveira da Silva, Riccardo Scattolini:
Nonlinear MPC for Offset-Free Tracking of systems learned by GRU Neural Networks. CoRR abs/2103.02383 (2021) - [i21]Fabio Bonassi, Riccardo Scattolini:
Recurrent neural network-based Internal Model Control of unknown nonlinear stable systems. CoRR abs/2108.04585 (2021) - [i19]Fabio Bonassi, Marcello Farina, Jing Xie, Riccardo Scattolini:
On Recurrent Neural Networks for learning-based control: recent results and ideas for future developments. CoRR abs/2111.13557 (2021) - 2020
- [c46]Fabio Bonassi, Alessio La Bella, Lorenzo Fagiano, Riccardo Scattolini, Donato Zarrilli, Pablo Almaleck:
Software-in-the-loop testing of a distributed optimal scheduling strategy for microgrids' aggregators. ISGT-Europe 2020: 985-989 - [c45]Fabio Bonassi, Enrico Terzi, Marcello Farina, Riccardo Scattolini:
LSTM Neural Networks: Input to State Stability and Probabilistic Safety Verification. L4DC 2020: 85-94 - [i16]Fabio Bonassi, Marcello Farina, Riccardo Scattolini:
On the stability properties of Gated Recurrent Units neural networks. CoRR abs/2011.06806 (2020) - [i15]Fabio Bonassi, Marcello Farina, Riccardo Scattolini:
Stability of discrete-time feed-forward neural networks in NARX configuration. CoRR abs/2012.03741 (2020) - 2019
- [i9]Fabio Bonassi, Enrico Terzi, Marcello Farina, Riccardo Scattolini:
LSTM Neural Networks: Input to State Stability and Probabilistic Safety Verification. CoRR abs/1912.04377 (2019)
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