140 citations · 401 across the 23 of their papers we have counts for
6 papers · 1 filter
Computation of Parameter Dependent Robust Invariant Sets for LPV Models with Guaranteed Performance
Ankit Gupta, Manas Mejari, Paolo Falcone +1
This paper presents an iterative algorithm to compute a Robust Control Invariant (RCI) set, along with an invariance-inducing control law, for Linear Parameter-Varying (LPV) system…
Preferential Bayesian optimisation with Skew Gaussian Processes
Alessio Benavoli, Dario Azzimonti, Dario Piga
Preferential Bayesian optimisation (PBO) deals with optimisation problems where the objective function can only be accessed via preference judgments, such as "this is better than t…
Continuous-time system identification with neural networks: Model structures and fitting criteria
Marco Forgione, Dario Piga
This paper presents tailor-made neural model structures and two custom fitting criteria for learning dynamical systems. The proposed framework is based on a representation of the s…
dynoNet: a neural network architecture for learning dynamical systems
Marco Forgione, Dario Piga
This paper introduces a network architecture, called dynoNet, utilizing linear dynamical operators as elementary building blocks. Owing to the dynamical nature of these blocks, dyn…
Skew Gaussian Processes for Classification
Alessio Benavoli, Dario Azzimonti, Dario Piga
Gaussian processes (GPs) are distributions over functions, which provide a Bayesian nonparametric approach to regression and classification. In spite of their success, GPs have lim…
Preference-based MPC calibration
Mengjia Zhu, Alberto Bemporad, Dario Piga
Automating the calibration of the parameters of a control policy by means of global optimization requires quantifying a closed-loop performance function. As this can be impractical…