most citedScenario optimization for optimal training of Echo State Networks

4 citations · 4 across the 2 of their papers we have counts for

collaborators

6 papers

eess.SY2020

A Hierarchical Architecture for the Coordination of an Ensemble of Steam Generators

Stefano Spinelli, Elia Longoni, Marcello Farina +3

This work presents a hierarchical architecture for the optimal management of an ensemble of steam generators, which needs to jointly sustain a common load. The coordination of inde…

eess.SY2020

A feedback linearisation algorithm for single-track models with structural stability properties

Luca Bascetta, Marcello Farina, Alessandro Gabrielli +1

This paper proposes a feedback linearizing law for single-track dynamic models, allowing the design of a trajectory tracking controller exploiting linear control theory. The main c…

eess.SY20194 cited

Scenario optimization for optimal training of Echo State Networks

Luca Bugliari Armenio, Lorenzo Fagiano, Enrico Terzi +2

Echo State Networks (ESNs) are widely-used Recurrent Neural Networks. They are dynamical systems including, in state-space form, a nonlinear state equation and a linear output tran…

eess.SY2019

LSTM Neural Networks: Input to State Stability and Probabilistic Safety Verification

Fabio Bonassi, Enrico Terzi, Marcello Farina +1

The goal of this paper is to analyze Long Short Term Memory (LSTM) neural networks from a dynamical system perspective. The classical recursive equations describing the evolution o…

cs.RO2019

Nonlinear Model Predictive Control with Enhanced Actuator Model for Multi-Rotor Aerial Vehicles with Generic Designs

Davide Bicego, Jacopo Mazzetto, Ruggero Carli +2

In this paper, we propose, discuss, and validate an online Nonlinear Model Predictive Control (NMPC) method for multi-rotor aerial systems with arbitrarily positioned and oriented…

eess.SY2019

Model predictive control design for dynamical systems learned by Long Short-Term Memory Networks

Enrico Terzi, Fabio Bonassi, Marcello Farina +1

This paper analyzes the stability-related properties of Long Short-Term Memory (LSTM) networks and investigates their use as the model of the plant in the design of Model Predictiv…