7 papers · 1 filter
State-action control barrier functions: Imposing safety on learning-based control with low online computational costs
Kanghui He, Shengling Shi, Ton van den Boom +1
Learning-based control with safety guarantees usually requires real-time safety certification and modifications of possibly unsafe learning-based policies. The control barrier func…
Multi-Agent Reinforcement Learning via Distributed MPC as a Function Approximator
Samuel Mallick, Filippo Airaldi, Azita Dabiri +1
This paper presents a novel approach to multi-agent reinforcement learning (RL) for linear systems with convex polytopic constraints. Existing work on RL has demonstrated the use o…
Reinforcement Learning with Model Predictive Control for Highway Ramp Metering
Filippo Airaldi, Bart De Schutter, Azita Dabiri
In the backdrop of an increasingly pressing need for effective urban and highway transportation systems, this work explores the synergy between model-based and learning-based strat…
Proactive Emergency Collision Avoidance for Automated Driving in Highway Scenarios
Leila Gharavi, Azita Dabiri, Jelske Verkuijlen +2
Uncertainty in the behavior of other traffic participants is a crucial factor in collision avoidance for automated driving; here, stochastic metrics could avoid overly conservative…
A Behavioral Perspective on Models of Linear Dynamical Networks with Manifest Variables
Shengling Shi, Zhiyong Sun, Bart De Schutter
Networks of dynamical systems play an important role in various domains and have motivated many studies on the control and analysis of linear dynamical networks. For linear network…
Efficient MPC for Emergency Evasive Maneuvers, Part II: Comparative Assessment for Hybrid Control
Leila Gharavi, Bart De Schutter, Simone Baldi
Optimization-based approaches such as Model Predictive Control (MPC) are promising approaches in proactive control for safety-critical applications with changing environments such…