104 citations · 125 across the 8 of their papers we have counts for
11 papers
Imitation Learning with Safety and L2 Stability Certificates for Boundary Control of Reaction-Diffusion PDEs
Paulo Henrique Foganholo Biazetto, Mirko Fiacchini, Christophe Prieur +1
This paper proposes an imitation learning (IL) framework for synthesizing neural network (NN) controllers that achieve boundary stabilization of systems governed by reaction-diffus…
Covariance Propagation and Stabilization for Tube-Based Stochastic MPC under Parametric and Additive Uncertainties
Kaouther Moussa, Mirko Fiacchini
This work addresses an SMPC-oriented characterization of the error covariance dynamics for linear discrete-time systems subject to both additive and parametric stochastic uncertain…
Automated Multi-Drugs Administration During Total Intravenous Anesthesia Using Multi-Model Predictive Control
Bob Aubouin-Pairault, Mirko Fiacchini, Thao Dang
In this paper, a multi-model predictive control approach is used to automate the co-administration of propofol and remifentanil from bispectral index measurement during general ane…
Output Regulation of Stochastic Sampled-Data Systems with Post-processing Internal Model
Himadri Basu, Francesco Ferrante, Mirko Fiacchini
This paper deals with the output regulation problem (ORP) of a linear time-invariant (LTI) system in the presence of sporadically sampled measurement streams with the inter-samplin…
The Ockham's razor applied to COVID-19 model fitting French data
Mirko Fiacchini, Mazen Alamir
This paper presents a data-based simple model for fitting the available data of the Covid-19 pandemic evolution in France. The time series concerning the 13 regions of mainland Fra…
Probabilistically Certified Region of Attraction of a Tumor Growth Model with Combined Chemo- and Immunotherapy
Kaouther Moussa, Mirko Fiacchini, Mazen Alamir
This paper deals with the estimation of regions of attraction (RoAs) under parametric uncertainties for a cancer growth model with combined therapies. We propose a framework of pro…
Probabilistic reachable and invariant sets for linear systems with correlated disturbance
Mirko Fiacchini, Teodoro Alamo
In this paper a constructive method to determine and compute probabilistic reachable and invariant sets for linear discrete-time systems, excited by a stochastic disturbance, is pr…
Computing control invariant sets in high dimension is easy
Mirko Fiacchini, Mazen Alamir
In this paper we consider the problem of computing control invariant sets for linear controlled high-dimensional systems with constraints on the input and on the states. Set inclus…
LMI-Based Reset Unknown Input Observer for State Estimation of Linear Uncertain Systems
Iman Hosseini, Alireza Khayatian, Paknoush Karimaghaee +2
This paper proposes a novel kind of Unknown Input Observer (UIO) called Reset Unknown Input Observer (R-UIO) for state estimation of linear systems in the presence of disturbance u…
Computing control invariant sets is easy
Mirko Fiacchini, Mazen Alamir
In this paper we consider the problem of computing control invariant sets for linear controlled systems with constraints on the input and on the states. We focus in particular on t…
Observer-Based Feedback Stabilization of Linear Systems with Event-triggered Sampling and Dynamic Quantization
Aneel Tanwani, Christophe Prieur, Mirko Fiacchini
We consider the problem of output feedback stabilization in linear systems when the measured outputs and control inputs are subject to event-triggered sampling and dynamic quantiza…