9 papers
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…
Adaptive Stepsizes With Certified Convergence in Distributed Gradient Tracking With Quadratic Costs
Yifan Wang, Luca Ballotta, Ruggero Carli +3
In this work, we propose an adaptive stepsize rule with guaranteed convergence for Distributed Gradient Tracking applied to scalar quadratic problems with heterogeneous curvatures.…
Pursuing Optimal Stepsize in Adaptive Gradient-Based Quadratic Optimization
Yifan Wang, Luca Ballotta, Ruggero Carli +2
In this paper, we address the problem of achieving fast convergence in gradient descent for quadratic functions without relying on a priori knowledge of global function parameters.…
Timescale Separation Through the Lens of Operator Theory
Guido Carnevale, Nicola Bastianello, Luca Schenato +2
Timescale separation is a powerful tool for analyzing interconnected dynamical systems. Meanwhile, operator theory provides a general framework for studying the convergence of iter…
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…