4 citations · 4 across the 2 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…
Echo State Networks: analysis, training and predictive control
Luca Bugliari Armenio, Enrico Terzi, Marcello Farina +1
The goal of this paper is to investigate the theoretical properties, the training algorithm, and the predictive control applications of Echo State Networks (ESNs), a particular kin…
Learning-based predictive control for linear systems: a unitary approach
Enrico Terzi, Lorenzo Fagiano, Marcello Farina +1
A comprehensive approach addressing identification and control for learningbased Model Predictive Control (MPC) for linear systems is presented. The design technique yields a data-…