257 citations · 996 across the 51 of their papers we have counts for
7 papers · 1 filter
Failure-Mechanism Transferability of Cumulative-Damage Features for Health State Estimation of SiC Power Modules
Mattia Scarpa, Evgeny Kusmenko, Francesco Toso +3
Data-driven health-state estimators for SiC (Silica-Carbide) power modules typically report their performance on a single accelerated-aging campaign, and how that performance trans…
Physics-Informed Condition Monitoring of SiC Power Modules
Mattia Scarpa, Evgeny Kusmenko, Francesco Toso +3
Silicon carbide (SiC) power modules are increasingly deployed in automotive traction inverters, where condition monitoring is essential to prevent in-service failures. Despite exte…
Data-driven Power Loss Identification through Physics-Based Thermal Model Backpropagation
Mattia Scarpa, Francesco Pase, Ruggero Carli +2
Digital twins for power electronics require accurate power losses whose direct measurements are often impractical or impossible in real-world applications. This paper presents a no…
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…
Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models
Alberto Dalla Libera, Fabio Amadio, Daniel Nikovski +2
In this paper, we consider the use of black-box Gaussian process (GP) models for trajectory tracking control based on feedback linearization, in the context of mechanical systems.…
Distributed Partitioned Big-Data Optimization via Asynchronous Dual Decomposition
Ivano Notarnicola, Ruggero Carli, Giuseppe Notarstefano
In this paper we consider a novel partitioned framework for distributed optimization in peer-to-peer networks. In several important applications the agents of a network have to sol…
Partition-based Distributed Kalman Filter with plug and play features
Marcello Farina, Ruggero Carli
In this paper we propose a novel partition-based distributed state estimation scheme for non-overlapping subsystems based on Kalman filter. The estimation scheme is designed in ord…