67 citations · 324 across the 46 of their papers we have counts for
51 papers
Distributed Motion Planning for Multi-Robot Systems under Topological Constraints
Gianpietro Battocletti, Dimitris Boskos, Dimos V. Dimarogonas +1
Efficient and distributed coordination of mobile robots is one of the main challenges in multi-robot systems. Topological constraints, often expressed as topological braids, are a…
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…
Asynchronous Model Predictive Control Under Model Mismatch: Stability and Performance Guarantees
Changrui Liu, Anil Alan, Shengling Shi +1
Certainty-equivalence model predictive control (CE-MPC) is widely used for its simplicity and efficiency, but theoretical guarantees under asynchronous feedback remain limited. Thi…
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,…
On the Value Function of Infinite-Horizon Optimal Control of Piecewise Affine Systems
Francesco Cordiano, Kanghui He, Bart De Schutter
In this paper, we study the structure of the value function in constrained infinite-time optimal control (CITOC) problems of piecewise affine (PWA) systems, with or $\ell_…
Entanglement-Free Trajectory Planning for Tethered Mobile Robots with a Slack Tether
Gianpietro Battocletti, Dimitris Boskos, Bart De Schutter
In motion planning algorithms for tethered mobile robots, the entanglement state of the tether is a critical aspect to consider during the planning phase. This is particularly impo…
Learning-Based Stochastic Optimal Control with Infinite-Horizon Probabilistic Constraints
Francesco Cordiano, Kanghui He, Bart De Schutter
In this paper, we consider stochastic optimal control problems with infinite-horizon joint chance constraints. By means of an appropriate state augmentation, we reformulate the ori…
Current Practices in Electricy Demand and Charging Scheduling for On-Road Electric Fleet Operations: An Industry-Wide Review
Joost Commandeur, Bart De Schutter, Neil Yorke-Smith
The electrification of on-road fleet logistics promises improved air quality, lower noise emissions, major climate benefits, increased energy flexibility through the use of locally…
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…
Model Predictive Control and Moving Horizon Estimation using Statistically Weighted Data-Based Ensemble Models
Laura Boca de Giuli, Samuel Mallick, Alessio La Bella +3
This paper presents a model predictive control (MPC) framework leveraging an ensemble of data-based models to optimally control complex systems under multiple operating conditions.…
Second-Order MPC-Based Distributed Q-Learning
Samuel Mallick, Filippo Airaldi, Azita Dabiri +1
The state of the art for model predictive control (MPC)-based distributed Q-learning is limited to first-order gradient updates of the MPC parameterization. In general, using secon…
Predictive control barrier functions for piecewise affine systems with non-smooth constraints
Kanghui He, Anil Alan, Shengling Shi +2
Obtaining control barrier functions (CBFs) with large safe sets for complex nonlinear systems and constraints is a challenging task. Predictive CBFs address this issue by using an…
Approximate Model Predictive Control for Microgrid Energy Management via Imitation Learning
Changrui Liu, Shengling Shi, Anil Alan +2
Efficient energy management is essential for reliable and sustainable microgrid operation amid increasing renewable integration. In this paper, an imitation learning-based framewor…
Robust Adaptive Discrete-Time Control Barrier Certificate
Changrui Liu, Anil Alan, Shengling Shi +1
This work develops a robust adaptive control strategy for discrete-time systems using Control Barrier Functions (CBFs) to ensure safety under parametric model uncertainty and distu…
WaveletInception Networks for on-board Vibration-Based Infrastructure Health Monitoring
Reza Riahi Samani, Alfredo Nunez, Bart De Schutter
This paper presents a deep learning framework for analyzing on board vibration response signals in infrastructure health monitoring. The proposed WaveletInception-BiGRU network use…
Distributed model predictive control without terminal cost under inexact distributed optimization
Xiaoyu Liu, Dimos V. Dimarogonas, Changxin Liu +2
This paper presents a novel distributed model predictive control (MPC) formulation without terminal cost and a corresponding distributed synthesis approach for distributed linear d…
Learning-based model predictive control for passenger-oriented train rescheduling with flexible train composition
Xiaoyu Liu, Caio Fabio Oliveira da Silva, Azita Dabiri +2
This paper focuses on passenger-oriented real-time train rescheduling, considering flexible train composition and rolling stock circulation, by integrating learning-based and optim…
Sensitivity Analysis for Piecewise-Affine Approximations of Nonlinear Programs with Polytopic Constraints
Leila Gharavi, Changrui Liu, Bart De Schutter +1
Nonlinear Programs (NLPs) are prevalent in optimization-based control of nonlinear systems. Solving general NLPs is computationally expensive, necessitating the development of fast…
Stability and Performance Analysis of Model Predictive Control of Uncertain Linear Systems
Changrui Liu, Shengling Shi, Bart De Schutter
Model mismatch often poses challenges in model-based controller design. This paper investigates model predictive control (MPC) of uncertain linear systems with input constraints, f…
Scenario Reduction with Guarantees for Stochastic Optimal Control of Linear Systems
Francesco Cordiano, Bart De Schutter
Scenario reduction algorithms can be an effective means to provide a tractable description of the uncertainty in optimal control problems. However, they might significantly comprom…
Distributed Model Predictive Control for Piecewise Affine Systems Based on Switching ADMM
Samuel Mallick, Azita Dabiri, Bart De Schutter
This paper presents a novel approach for distributed model predictive control (MPC) for piecewise affine (PWA) systems. Existing approaches rely on solving mixed-integer optimizati…
A Benchmark for the Application of Distributed Control Techniques to the Electricity Network of the European Economic Area
A. Riccardi, L. Laurenti, B. De Schutter
The European Economic Area Electricity Network Benchmark (EEA-ENB) is a multi-area power system representing the European network of transmission systems for electricity to facilit…
Entanglement Definitions for Tethered Robots: Exploration and Analysis
Gianpietro Battocletti, Dimitris Boskos, Domagoj Tolić +2
In this article we consider the problem of tether entanglement for tethered mobile robots. One of the main risks of using a tethered connection between a mobile robot and an anchor…
A Comparison Benchmark for Distributed Hybrid MPC Control Methods: Distributed Vehicle Platooning
Samuel Mallick, Azita Dabiri, Bart De Schutter
Distributed model predictive control (MPC) is currently being investigated as a solution to the important control challenge presented by networks of hybrid dynamical systems. Howev…