67 citations · 138 across the 9 of their papers we have counts for
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…
A Model Predictive Control Framework for Assisted Vehicle Drifting
Marco Cortese, Antonio Gallina, Matteo Grandin +3
Model Predictive Control (MPC) has been widely applied to autonomous vehicle drifting. Assisted drifting, that is where the driver remains in the loop, is still comparatively under…
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…
A Sim-to-Real Vision-based Lane Keeping System for a 1:10-scale Autonomous Vehicle
Antonio Gallina, Matteo Grandin, Angelo Cenedese +1
In recent years, several competitions have highlighted the need to investigate vision-based solutions to address scenarios with functional insufficiencies in perception, world mode…
A Learning-based Nonlinear Model Predictive Controller for a Real Go-Kart based on Black-box Dynamics Modeling through Gaussian Processes
Enrico Picotti, Enrico Mion, Alberto Dalla Libera +5
Lately, Nonlinear Model Predictive Control (NMPC)has been successfully applied to (semi-) autonomous driving problems and has proven to be a very promising technique. However, accu…
An Efficient Move Blocking Strategy for Multiple Shooting based Nonlinear Model Predictive Control
Yutao Chen, Nicolo Scarabottolo, Mattia Bruschetta +1
Move blocking (MB) is a widely used strategy to reduce the degrees of freedom of the Optimal Control Problem (OCP) arising in receding horizon control. The size of the OCP is reduc…
MATMPC - A MATLAB Based Toolbox for Real-time Nonlinear Model Predictive Control
Yutao Chen, Mattia Bruschetta, Enrico Picotti +1
In this paper we introduce MATMPC, an open source software built in MATLAB for nonlinear model predictive control (NMPC). It is designed to facilitate modelling, controller design…
An Adaptive Partial Sensitivity Updating Scheme for Fast Nonlinear Model Predictive Control
Yutao Chen, Mattia Bruschetta, Davide Cuccato +1
In recent years, efficient optimization algorithms for Nonlinear Model Predictive Control (NMPC) have been proposed, that significantly reduce the on-line computational time. In pa…