1 citations · 3 across the 9 of their papers we have counts for
9 papers
Nonlinear System Identification Nano-drone Benchmark
Riccardo Busetto, Elia Cereda, Marco Forgione +3
We introduce a benchmark for system identification based on 75k real-world samples from the Crazyflie 2.1 Brushless nano-quadrotor, a sub-50g aerial vehicle widely adopted in robot…
Learning Low-Dimensional Embeddings for Black-Box Optimization
Riccardo Busetto, Manas Mejari, Marco Forgione +2
When gradient-based methods are impractical, black-box optimization (BBO) provides a valuable alternative. However, BBO often struggles with high-dimensional problems and limited t…
In-Context Learning for Zero-Shot Speed Estimation of BLDC motors
Alessandro Colombo, Riccardo Busetto, Valentina Breschi +3
Accurate speed estimation in sensorless brushless DC motors is essential for high-performance control and monitoring, yet conventional model-based approaches struggle with system n…
One controller to rule them all
Riccardo Busetto, Valentina Breschi, Marco Forgione +2
Imagine having a system to control and only know that it belongs to a certain class of dynamical systems. Would it not be amazing to simply plug in a controller and have it work as…
Meta-learning of data-driven controllers with automatic model reference tuning: theory and experimental case study
Riccardo Busetto, Valentina Breschi, Federica Baracchi +1
Data-driven control offers a viable option for control scenarios where constructing a system model is expensive or time-consuming. Nonetheless, many of these algorithms are not ent…
Hawkes-based cryptocurrency forecasting via Limit Order Book data
Raffaele Giuseppe Cestari, Filippo Barchi, Riccardo Busetto +2
Accurately forecasting the direction of financial returns poses a formidable challenge, given the inherent unpredictability of financial time series. The task becomes even more ard…
In-context learning of state estimators
Riccardo Busetto, Valentina Breschi, Marco Forgione +2
State estimation has a pivotal role in several applications, including but not limited to advanced control design. Especially when dealing with nonlinear systems state estimation i…
Meta-learning for model-reference data-driven control
Riccardo Busetto, Valentina Breschi, Simone Formentin
One-shot direct model-reference control design techniques, like the Virtual Reference Feedback Tuning (VRFT) approach, offer time-saving solutions for the calibration of fixed-stru…
META-SMGO-: similarity as a prior in black-box optimization
Riccardo Busetto, Valentina Breschi, Simone Formentin
When solving global optimization problems in practice, one often ends up repeatedly solving problems that are similar to each others. By providing a rigorous definition of similari…