53 citations · 151 across the 36 of their papers we have counts for
16 papers · 1 filter
The Bayesian Separation Principle for Data-driven Control
Giacomo Baggio, Ruggero Carli, Riccardo Alessandro Grimaldi +1
In this paper we investigate the existence of a separation principle between model identification and control design in the context of model predictive control. First, we clarify t…
Absolute integrability of Mercer kernels is only sufficient for RKHS stability
Mauro Bisiacco, Gianluigi Pillonetto
Reproducing kernel Hilbert spaces (RKHSs) are special Hilbert spaces in one-to-one correspondence with positive definite maps called kernels. They are widely employed in machine le…
On the stability test for reproducing kernel Hilbert spaces
Mauro Bisiacco, Gianluigi Pillonetto
Reproducing kernel Hilbert spaces (RKHSs) are special Hilbert spaces where all the evaluation functionals are linear and bounded. They are in one-to-one correspondence with positiv…
Sliding-mode theory under feedback constraints and the problem of epidemic control
Mauro Bisiacco, Gianluigi Pillonetto
One of the most important branches of nonlinear control theory is the so-called sliding-mode. Its aim is the design of a (nonlinear) feedback law that brings and maintains the stat…
COVID-19 epidemic control using short-term lockdowns for collective gain
Mauro Bisiacco, Gianluigi Pillonetto
While many efforts are currently devoted to vaccines development and administration, social distancing measures, including severe restrictions such as lockdowns, remain fundamental…
Tracking the time course of reproduction number and lockdown's effect during SARS-CoV-2 epidemic: nonparametric estimation
Gianluigi Pillonetto, Mauro Bisiacco, Giorgio Palù +1
Accurate modeling of lockdown effects on SARS-CoV-2 epidemic evolution is a key issue in order e.g. to inform health-care decisions on emergency management. The compartmental and s…