238 citations · 387 across the 34 of their papers we have counts for
14 papers · 1 filter
Collective Tube Model Predictive Control With Distribution-Free Joint Safety Certificates
Giuseppe C. Calafiore
Data-calibrated stochastic MPC typically builds separate risk margins for many events along the horizon, such as times, facets, state/input components, or obstacles, and then combi…
Exact Risk-Complexity Laws for Projective Boundaries in Scenario Optimization and Distribution-Free Certification
Giuseppe C. Calafiore
Scenario optimization, conformal prediction, and related distribution-free certification methods use finite samples to construct decisions or prediction sets with violation-risk gu…
Bridging Conformal Prediction and Scenario Optimization: Discarded Constraints and Modular Risk Allocation
Giuseppe C. Calafiore
Scenario optimization and conformal prediction share a common goal, that is, turning finite samples into safety margins. Yet, different terminology often obscures the connection be…
Geometry-Aware Set-Membership Multilateration: Directional Bounds and Anchor Selection
Giuseppe C. Calafiore
In this paper, we study anchor selection for range-based localization under unknown-but-bounded measurement errors. We start from the convex localization set $\X=\Xd\cap\Hset$ rece…
A kernel-based approach to physics-informed nonlinear system identification
Cesare Donati, Martina Mammarella, Giuseppe C. Calafiore +3
This paper presents a kernel-based framework for physics-informed nonlinear system identification. The key contribution is a structured methodology that extends kernel-based techni…
Equilibrium Selection in Replicator Equations Using Adaptive-Gain Control
Lorenzo Zino, Mengbin Ye, Giuseppe Carlo Calafiore +1
In this paper, we deal with the equilibrium selection problem, which amounts to steering a population of individuals engaged in strategic game-theoretic interactions to a desired c…
On Adaptive-Gain Control of Replicator Dynamics in Population Games
Lorenzo Zino, Mengbin Ye, Alessandro Rizzo +1
Controlling evolutionary game-theoretic dynamics is a problem of paramount importance for the systems and control community, with several applications spanning from social science…
New Results on Delay Robustness of Consensus Algorithms
Anton V. Proskurnikov, Guiseppe Calafiore
Consensus of autonomous agents is a benchmark problem in cooperative control. In this paper, we consider standard continuous-time averaging consensus policies (or Laplacian flows)…
Nonlinear system identification in Sobolev spaces
Carlo Novara, Angelo Nicolì, Giuseppe C. Calafiore
We consider the problem of deriving from experimental data an approximation of an unknown function, whose derivatives also approximate the unknown function derivatives. Solving thi…
Recurrent Averaging Inequalities in Multi-Agent Control and Social Dynamics Modeling
Anton V. Proskurnikov, Giuseppe Calafiore, Ming Cao
Many multi-agent control algorithms and dynamic agent-based models arising in natural and social sciences are based on the principle of iterative averaging. Each agent is associate…
Leading Impulse Response Identification via the Weighted Elastic Net Criterion
Giuseppe C. Calafiore, Carlo Novara, Michele Taragna
This paper deals with the problem of finding a low-complexity estimate of the impulse response of a linear time-invariant discrete-time dynamic system from noise-corrupted input-ou…
On Repetitive Scenario Design
Giuseppe C. Calafiore
Repetitive Scenario Design (RSD) is a randomized approach to robust design based on iterating two phases: a standard scenario design phase that uses scenarios (design samples),…
Sparse Identification of Posynomial Models
Giuseppe C. Calafiore, Laurent El Ghaoui, Carlo Novara
Posynomials are nonnegative combinations of monomials with possibly fractional and both positive and negative exponents. Posynomial models are widely used in various engineering de…
Robust Model Predictive Control via Scenario Optimization
Giuseppe C. Calafiore, Lorenzo Fagiano
This paper discusses a novel probabilistic approach for the design of robust model predictive control (MPC) laws for discrete-time linear systems affected by parametric uncertainty…