12 papers
Temporal Logic Control of Nonlinear Stochastic Systems with Online Performance Optimization
Alessandro Riccardi, Thom Badings, Luca Laurenti +2
The deployment of autonomous systems in safety-critical environments requires control policies that guarantee satisfaction of complex control specifications. These systems are comm…
Dodging the Moose: Experimental Insights in Real-Life Automated Collision Avoidance
Leila Gharavi, Simone Baldi, Yuki Hosomi +4
The sudden appearance of a static obstacle on the road, i.e. the moose test, is a well-known emergency scenario in collision avoidance for automated driving. Model Predictive Contr…
Dynamics of Implicit Time-Invariant Max-Min-Plus-Scaling Discrete-Event Systems
Sreeshma Markkassery, Ton van den Boom, Bart De Schutter
Max-min-plus-scaling (MMPS) systems generalize max-plus, min-plus and max-min-plus models with more flexibility in modelling discrete-event dynamics. Especially, implicit MMPS mode…
Reinforcement Learning with Distributed MPC for Fuel-Efficient Platoon Control with Discrete Gear Transitions
Samuel Mallick, Gianpietro Battocletti, Dimitris Boskos +2
Cooperative control of groups of autonomous vehicles (AVs), i.e., platoons, is a promising direction to improving the efficiency of autonomous transportation systems. In this conte…
Model Predictive Control for Cooperative Docking Between Autonomous Surface Vehicles with Disturbance Rejection
Gianpietro Battocletti, Dimitris Boskos, Bart De Schutter
Uncrewed Surface Vehicles (USVs) are a popular and efficient type of marine craft that find application in a large number of water-based tasks. When multiple USVs operate in the sa…
Efficient Computation of a Continuous Topological Model of the Configuration Space of Tethered Mobile Robots
Gianpietro Battocletti, Dimitris Boskos, Bart De Schutter
Despite the attention that the problem of path planning for tethered robots has garnered in the past few decades, the approaches proposed to solve it typically rely on a discrete r…
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…
Uncertainty Partitioning with Probabilistic Feasibility and Performance Guarantees for Chance-Constrained Optimization
Francesco Cordiano, Matin Jafarian, Bart De Schutter
We propose a novel distribution-free scheme to solve optimization problems where the goal is to minimize the expected value of a cost function subject to probabilistic constraints.…
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…
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…