activity
20192022
most citedAutonomous docking using direct optimal control

55 citations · 59 across the 11 of their papers we have counts for

collaborators

22 papers

eess.SY2022

Conflict-free Charging and Real-time Control for an Electric Bus Network

Rémi Lacombe, Nikolce Murgovski, Sébastien Gros +1

The rapid adoption of electric buses by transit agencies around the world is leading to new challenges in the planning and operation of bus networks. In particular, the limited dri…

math.OC2022

Solving Mission-Wide Chance-Constrained Optimal Control Using Dynamic Programming

Kai Wang, Sebastien Gros

This paper aims to provide a Dynamic Programming (DP) approach to solve the Mission-Wide Chance-Constrained Optimal Control Problems (MWCC-OCP). The mission-wide chance constraint…

eess.SY20221 cited

Bridging the gap between QP-based and MPC-based RL

Shambhuraj Sawant, Sebastien Gros

Reinforcement learning methods typically use Deep Neural Networks to approximate the value functions and policies underlying a Markov Decision Process. Unfortunately, DNN-based RL…

eess.SY2022

Functional Stability of Discounted Markov Decision Processes Using Economic MPC Dissipativity Theory

Arash Bahari Kordabad, Sebastien Gros

This paper discusses the functional stability of closed-loop Markov Chains under optimal policies resulting from a discounted optimality criterion, forming Markov Decision Processe…

cs.LG2022

Quasi-Newton Iteration in Deterministic Policy Gradient

Arash Bahari Kordabad, Hossein Nejatbakhsh Esfahani, Wenqi Cai +1

This paper presents a model-free approximation for the Hessian of the performance of deterministic policies to use in the context of Reinforcement Learning based on Quasi-Newton st…

eess.SY20212 cited

Multi-agent Battery Storage Management using MPC-based Reinforcement Learning

A. Bahari Kordabad, W. Cai, S. Gros

In this paper, we present the use of Model Predictive Control (MPC) based on Reinforcement Learning (RL) to find the optimal policy for a multi-agent battery storage system. A time…