28 citations · 77 across the 23 of their papers we have counts for
10 papers · 1 filter
Safe model-based Reinforcement Learning via Model Predictive Control and Control Barrier Functions
Kerim Dzhumageldyev, Filippo Airaldi, Azita Dabiri
Optimal control strategies are often combined with safety certificates to ensure both performance and safety in safety-critical systems. A prominent example is combining Model Pred…
Adaptive Tuning of Parameterized Traffic Controllers via Multi-Agent Reinforcement Learning
Giray Önür, Azita Dabiri, Bart De Schutter
Effective traffic control is essential for mitigating congestion in transportation networks. Conventional traffic management strategies, including route guidance and ramp metering,…
Model Predictive Control and Moving Horizon Estimation using Statistically Weighted Data-Based Ensemble Models
Laura Boca de Giuli, Samuel Mallick, Alessio La Bella +3
This paper presents a model predictive control (MPC) framework leveraging an ensemble of data-based models to optimally control complex systems under multiple operating conditions.…
Second-Order MPC-Based Distributed Q-Learning
Samuel Mallick, Filippo Airaldi, Azita Dabiri +1
The state of the art for model predictive control (MPC)-based distributed Q-learning is limited to first-order gradient updates of the MPC parameterization. In general, using secon…
A state reduction approach for learning-based model predictive control for train rescheduling
Caio Fabio Oliveira da Silva, Xiaoyu Liu, Azita Dabiri +1
This paper proposes a state reduction method for learning-based model predictive control (MPC) for train rescheduling in urban rail transit systems. The state reduction integrates…
Distributed model predictive control without terminal cost under inexact distributed optimization
Xiaoyu Liu, Dimos V. Dimarogonas, Changxin Liu +2
This paper presents a novel distributed model predictive control (MPC) formulation without terminal cost and a corresponding distributed synthesis approach for distributed linear d…
Probabilistically safe and efficient model-based reinforcement learning
Filippo Airaldi, Bart De Schutter, Azita Dabiri
This paper proposes tackling safety-critical stochastic Reinforcement Learning (RL) tasks with a sample-based, model-based approach. At the core of the method lies a Model Predicti…
Learning-Based MPC for Fuel Efficient Control of Autonomous Vehicles with Discrete Gear Selection
Samuel Mallick, Gianpietro Battocletti, Qizhang Dong +2
Co-optimization of both vehicle speed and gear position via model predictive control (MPC) has been shown to offer benefits for fuel-efficient autonomous driving. However, optimizi…
Optimization-based Coordination of Traffic Lights and Automated Vehicles at Intersections
Azita Dabiri, Giray Önür, Sebastien Gros +1
This paper tackles the challenge of coordinating traffic lights and automated vehicles at signalized intersections, formulated as a constrained finite-horizon optimal control probl…
Learning-based model predictive control for passenger-oriented train rescheduling with flexible train composition
Xiaoyu Liu, Caio Fabio Oliveira da Silva, Azita Dabiri +2
This paper focuses on passenger-oriented real-time train rescheduling, considering flexible train composition and rolling stock circulation, by integrating learning-based and optim…