4 papers · 2 filters
Partitioning techniques for non-centralized predictive control: A systematic review and novel theoretical insights
Alessandro Riccardi, Luca Laurenti, Bart De Schutter
The partitioning problem is of central relevance for designing and implementing non-centralized Model Predictive Control (MPC) strategies for large-scale systems. These control app…
Learning State-Action Control Barrier Functions for Model-Free Control under Constraints
Kanghui He, Shengling Shi, Ton van den Boom +1
Ensuring constraint satisfaction for learning-based control is a critical challenge, especially in the model-free case. While safety filters address this challenge in the model-bas…
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…
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…