23 citations · 36 across the 7 of their papers we have counts for
9 papers
Policy Gradient Reinforcement Learning for Uncertain Polytopic LPV Systems based on MHE-MPC
Hossein Nejatbakhsh Esfahani, Sebastien Gros
In this paper, we propose a learning-based Model Predictive Control (MPC) approach for the polytopic Linear Parameter-Varying (LPV) systems with inexact scheduling parameters (as e…
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…
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…
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…
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…
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…
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…