28 citations · 77 across the 23 of their papers we have counts for
5 papers · 1 filter
Composite-Gradient Learning for Shared Control Authority Between Deep Reinforcement Learning and Model Predictive Control
Giray Önür, Azita Dabiri, Bart De Schutter
Integrated deep reinforcement learning (DRL) and model predictive control (MPC) methods are increasingly used to control autonomous systems by combining their complementary capabil…
Stochastic Nonlinear Model Predictive Control with Gaussian Mixture Uncertainty Propagation
Konstantinos Prattis, Luca Laurenti, Azita Dabiri
We propose a novel Stochastic Nonlinear Model Predictive Control (SNMPC) framework for nonlinear systems with additive noise. Building on recent advances in nonlinear uncertainty p…
Sharing the Control Authority Between Deep Reinforcement Learning and Model Predictive Control: Application to Multi-Class Transportation Networks
Giray Onur, Azita Dabiri, Bart De Schutter
Transportation networks, in particular multi-class transportation networks (i.e., networks with mixed vehicle types), are complex systems that are challenging to control. Recently,…
Integrated Online Monitoring and Adaptation of Process Model Predictive Controllers
Samuel Mallick, Laura Boca de de Giuli, Alessio La Bella +3
This paper addresses the design of an event-triggered, data-based, and performance-oriented adaption method for model predictive control (MPC). The performance of such a strategy s…
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…