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16 papers · 1 filter

cs.RO2025

Model Predictive Control for Cooperative Docking Between Autonomous Surface Vehicles with Disturbance Rejection

Gianpietro Battocletti, Dimitris Boskos, Bart De Schutter

Uncrewed Surface Vehicles (USVs) are a popular and efficient type of marine craft that find application in a large number of water-based tasks. When multiple USVs operate in the sa…

cs.RO2025

Efficient Computation of a Continuous Topological Model of the Configuration Space of Tethered Mobile Robots

Gianpietro Battocletti, Dimitris Boskos, Bart De Schutter

Despite the attention that the problem of path planning for tethered robots has garnered in the past few decades, the approaches proposed to solve it typically rely on a discrete r…

eess.SY2025

Iterative Cut-Based PWA Approximation of Multi-Dimensional Nonlinear Systems

Leila Gharavi, Bart De Schutter, Simone Baldi

PieceWise Affine (PWA) approximations for nonlinear functions have been extensively used for tractable, computationally efficient control of nonlinear systems. However, reaching a…

eess.SY2025

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…

eess.SY2025

Partitioning techniques for non-centralized predictive control: A systematic review and novel theoretical insights

Alessandro Riccardi, Luca Laurenti, Bart De Schutter

The partitioning problem is of central relevance for designing and implementing non-centralized Model Predictive Control (MPC) strategies for large-scale systems. These control app…

eess.SY2025

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…