Eco-VTF: Fuel-efficient vessel train formations for all-electric autonomous ships

Linying Chen, Ali Haseltalab, Vittorio Garofano, Rudy R. Negenborn

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

11 Citations (Scopus)
163 Downloads (Pure)


In this paper, a distributed control approach is proposed to enable fuel-efficient Vessel Train Formations (VTF) in inland waterways and port areas for addressing the efficiency and environmental issues of transport over water. For path tracking, collision avoidance, and consensus over the VTF speed a distributed Model Predictive Control (MPC) algorithm is adopted which uses the Alternating Direction Method of Multipliers (ADMM) to guarantee path following and consensus between vessels. The all-electric Direct Current (DC) configuration is considered for the Power and Propulsion Systems (PPS) of the autonomous vessels under study. Considering their PPS specification, the vessels negotiate with each other to agree on the most efficient speed for all the vessels in the VTF. Simulation results suggest that a significant amount of fuel saving can be obtained by using the proposed approach.

Original languageEnglish
Title of host publicationProceedings of the 18th European Control Conference (ECC 2019)
Place of PublicationPiscataway, NJ, USA
ISBN (Electronic)978-3-907144-00-8
Publication statusPublished - 2019
EventECC 2019: 18th European Control Conference - Napoli, Italy
Duration: 25 Jun 201928 Jun 2019


ConferenceECC 2019: 18th European Control Conference

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