29 citations · 160 across the 58 of their papers we have counts for
9 papers · 1 filter
Model Predictive Control with Multiple Constraint Horizons
Allan Andre do Nascimento, Han Wang, Antonis Papachristodoulou +1
We propose a Model Predictive Control (MPC) formulation for nonlinear systems without terminal penalty or dedicated stabilizing terminal set, in which state constraints are enforce…
Efficient Quantification of Time-Series Prediction Error: Optimal Selection Conformal Prediction
Boyu Pang, Kostas Margellos
Designing effective score functions in Conformal Prediction (CP) for time-series data remains challenging due to conservativeness and/or computational inefficiency. We propose Opti…
Data-Driven Performance Guarantees for Parametric Optimization Problems
Jingyi Huang, Paul Goulart, Kostas Margellos
We propose a data-driven method to establish probabilistic performance guarantees for parametric optimization problems solved via iterative algorithms. Our approach addresses two k…
Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens
Guido Carnevale, Filippo Fabiani, Filiberto Fele +2
We present a fully-distributed algorithm for Nash equilibrium seeking in aggregative games over networks. The proposed scheme endows each agent with a gradient-based scheme equippe…
Bridging conformal prediction and scenario optimization
Niall O'Sullivan, Licio Romao, Kostas Margellos
Conformal prediction and scenario optimization constitute two important classes of statistical learning frameworks to certify decisions made using data. They have found numerous ap…
Constraint Horizon in Model Predictive Control
Allan Andre Do Nascimento, Han Wang, Antonis Papachristodoulou +1
In this work, we propose a Model Predictive Control (MPC) formulation incorporating two distinct horizons: a prediction horizon and a constraint horizon. This approach enables a de…
Continuous-time Data-driven Barrier Certificate Synthesis
Luke Rickard, Alessandro Abate, Kostas Margellos
We consider the problem of verifying safety for continuous-time dynamical systems. Developing upon recent advancements in data-driven verification, we use only a finite number of s…
Predictive Control Barrier Functions: Bridging model predictive control and control barrier functions
Jingyi Huang, Han Wang, Kostas Margellos +1
In this paper, we establish a connection between model predictive control (MPC) techniques and Control Barrier Functions (CBFs). Recognizing the similarity between CBFs and Control…
Data-Driven Certificate Synthesis
Luke Rickard, Alessandro Abate, Kostas Margellos
We investigate the problem of verifying different properties of discrete time dynamical systems, namely, reachability, safety and reach-while-avoid. To achieve this, we adopt a dat…