341 citations · 793 across the 35 of their papers we have counts for
17 papers · 1 filter
Backstepping-based Integral Sliding Mode Control with Time Delay Estimation for Autonomous Underwater Vehicles
Hossein Nejatbakhsh Esfahani, Behdad Aminian, Esten Ingar Grøtli +1
The aim of this paper is to propose a high performance control approach for trajectory tracking of Autonomous Underwater Vehicles (AUVs). However, the controller performance can be…
A Semi-Distributed Interior Point Algorithm for Optimal Coordination of Automated Vehicles at Intersections
Robert Hult, Mario Zanon, Sebastien Gros +1
In this paper, we consider the optimal coordination of automated vehicles at intersections under fixed crossing orders. We formulate the problem using direct optimal control and ex…
Optimization of the Model Predictive Control Meta-Parameters Through Reinforcement Learning
Eivind Bøhn, Sebastien Gros, Signe Moe +1
Model predictive control (MPC) is increasingly being considered for control of fast systems and embedded applications. However, the MPC has some significant challenges for such sys…
Recursive Feasibility of Stochastic Model Predictive Control with Mission-Wide Probabilistic Constraints
Kai Wang, Sebastien Gros
This paper is concerned with solving chance-constrained finite-horizon optimal control problems, with a particular focus on the recursive feasibility issue of stochastic model pred…
Optimal Management of the Peak Power Penalty for Smart Grids Using MPC-based Reinforcement Learning
Wenqi Cai, Hossein N. Esfahani, Arash B. Kordabad +1
The cost of the power distribution infrastructures is driven by the peak power encountered in the system. Therefore, the distribution network operators consider billing consumers b…
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…
A New Dissipativity Condition for Asymptotic Stability of Discounted Economic MPC
Mario Zanon, Sébastien Gros
Economic Model Predictive Control has recently gained popularity due to its ability to directly optimize a given performance criterion, while enforcing constraint satisfaction for…
MPC-based Reinforcement Learning for a Simplified Freight Mission of Autonomous Surface Vehicles
Wenqi Cai, Arash B. Kordabad, Hossein N. Esfahani +2
In this work, we propose a Model Predictive Control (MPC)-based Reinforcement Learning (RL) method for Autonomous Surface Vehicles (ASVs). The objective is to find an optimal polic…
Verification of Dissipativity and Evaluation of Storage Function in Economic Nonlinear MPC using Q-Learning
Arash Bahari Kordabad, Sebastien Gros
In the Economic Nonlinear Model Predictive (ENMPC) context, closed-loop stability relates to the existence of a storage function satisfying a dissipation inequality. Finding the st…
Approximate Robust NMPC using Reinforcement Learning
Hossein Nejatbakhsh Esfahani, Arash Bahari Kordabad, Sebastien Gros
We present a Reinforcement Learning-based Robust Nonlinear Model Predictive Control (RL-RNMPC) framework for controlling nonlinear systems in the presence of disturbances and uncer…
Bias Correction in Deterministic Policy Gradient Using Robust MPC
Arash Bahari Kordabad, Hossein Nejatbakhsh Esfahani, Sebastien Gros
In this paper, we discuss the deterministic policy gradient using the Actor-Critic methods based on the linear compatible advantage function approximator, where the input spaces ar…
MPC-based Reinforcement Learning for Economic Problems with Application to Battery Storage
Arash Bahari Kordabad, Wenqi Cai, Sebastien Gros
In this paper, we are interested in optimal control problems with purely economic costs, which often yield optimal policies having a (nearly) bang-bang structure. We focus on polic…
Economic MPC of Markov Decision Processes: Dissipativity in Undiscounted Infinite-Horizon Optimal Control
Sébastien Gros, Mario Zanon
Economic Model Predictive Control (MPC) dissipativity theory is central to discussing the stability of policies resulting from minimizing economic stage costs. In its current form,…
Reinforcement Learning based on MPC/MHE for Unmodeled and Partially Observable Dynamics
Hossein Nejatbakhsh Esfahani, Arash Bahari Kordabad, Sebastien Gros
This paper proposes an observer-based framework for solving Partially Observable Markov Decision Processes (POMDPs) when an accurate model is not available. We first propose to use…
Reinforcement Learning based on Scenario-tree MPC for ASVs
Arash Bahari Kordabad, Hossein Nejatbakhsh Esfahani, Anastasios M. Lekkas +1
In this paper, we present the use of Reinforcement Learning (RL) based on Robust Model Predictive Control (RMPC) for the control of an Autonomous Surface Vehicle (ASV). The RL-MPC…
Reinforcement Learning of the Prediction Horizon in Model Predictive Control
Eivind Bøhn, Sebastien Gros, Signe Moe +1
Model predictive control (MPC) is a powerful trajectory optimization control technique capable of controlling complex nonlinear systems while respecting system constraints and ensu…
Stability-Constrained Markov Decision Processes Using MPC
Mario Zanon, Sébastien Gros, Michele Palladino
In this paper, we consider solving discounted Markov Decision Processes (MDPs) under the constraint that the resulting policy is stabilizing. In practice MDPs are solved based on s…