20 papers
Sharing the Control Authority Between Deep Reinforcement Learning and Model Predictive Control: Application to Multi-Class Transportation Networks
Giray Onur, Azita Dabiri, Bart De Schutter
Transportation networks, in particular multi-class transportation networks (i.e., networks with mixed vehicle types), are complex systems that are challenging to control. Recently,…
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…
Adaptive Tuning of Parameterized Traffic Controllers via Multi-Agent Reinforcement Learning
Giray Ãnür, 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,…
Nonmyopic Global Optimisation via Approximate Dynamic Programming
Filippo Airaldi, Bart De Schutter, Azita Dabiri
Global optimisation to optimise expensive-to-evaluate black-box functions without gradient information. Bayesian optimisation, one of the most well-known techniques, typically empl…
Integrated Online Monitoring and Adaptation of Process Model Predictive Controllers
Samuel Mallick, Laura Boca de de Giuli, Alessio La Bella +3
This paper addresses the design of an event-triggered, data-based, and performance-oriented adaption method for model predictive control (MPC). The performance of such a strategy s…