341 citations · 793 across the 35 of their papers we have counts for
7 papers · 1 filter
Learning for MPC with Stability & Safety Guarantees
Sébastien Gros, Mario Zanon
The combination of learning methods with Model Predictive Control (MPC) has attracted a significant amount of attention in the recent literature. The hope of this combination is to…
Optimization of the Model Predictive Control Update Interval Using Reinforcement Learning
Eivind Bøhn, Sebastien Gros, Signe Moe +1
In control applications there is often a compromise that needs to be made with regards to the complexity and performance of the controller and the computational resources that are…
Optimal model-based trajectory planning with static polygonal constraints
Andreas B. Martinsen, Anastasios M. Lekkas, Sebastien Gros
The main contribution of this paper is a novel method for planning globally optimal trajectories for dynamical systems subject to polygonal constraints. The proposed method is a hy…
Reinforcement Learning Based on Real-Time Iteration NMPC
Mario Zanon, Vyacheslav Kungurtsev, Sébastien Gros
Reinforcement Learning (RL) has proven a stunning ability to learn optimal policies from data without any prior knowledge on the process. The main drawback of RL is that it is typi…
Combining system identification with reinforcement learning-based MPC
Andreas B. Martinsen, Anastasios M. Lekkas, Sebastien Gros
In this paper we propose and compare methods for combining system identification (SYSID) and reinforcement learning (RL) in the context of data-driven model predictive control (MPC…
Reinforcement Learning for Mixed-Integer Problems Based on MPC
Sebastien Gros, Mario Zanon
Model Predictive Control has been recently proposed as policy approximation for Reinforcement Learning, offering a path towards safe and explainable Reinforcement Learning. This ap…
Safe Reinforcement Learning via Projection on a Safe Set: How to Achieve Optimality?
Sebastien Gros, Mario Zanon, Alberto Bemporad
For all its successes, Reinforcement Learning (RL) still struggles to deliver formal guarantees on the closed-loop behavior of the learned policy. Among other things, guaranteeing…