Rudy Negenborn Full Professor, Head of Section Latest news: RT @MSCActions: It's time to meet our #MSCA #RISE fellow of the week, @KatStankova! Kateřina is part of the FourCModelling project, which… How could we deal with uncertainty in dynamic models for ship manoevering? Read about how real-time learning and ad… https://t.co/ABgNolyU7h[More on Twitter] Main Publications Team & Themes Education Resume Personal

Transport Engineering and Logistics Dept. of Maritime and Transport Technology Delft University of Technology Mekelweg 2, 2628 CD  Delft The Netherlands Room B-3-300 How to reach Faculty 3mE How to reach my office tel: +31 (0) 15 27 86718 fax: +31 (0) 15 27 81397 contact form: Click here e-mail: r.r.negenborn@tudelft.nl secretary: Patty Bokop-van der Stap tel: +31 (0)15 27 86529 LinkedIn Twitter Autonomous Vessel Family Interacting Vessels Delfia-1 Star Delfia-1 [in action] Delfia-Amphibian SeaBax-Inside SeaBax-Outside Tito Neri Quality Care Hybrid Tug Friend of the Family: WUT-1 (Wuhan University of Technology) Friend of the Family: Vosper Perkasa (Wuhan University of Technology) Computational Logistics 2015 ICCL'15 - International Conference on Computational Logistics (ICCL) 2015 Delft, The Netherlands Main research interests: Coordination within and among transport hubs 4S Framework: Real-time coordination of Smart Equipment in Smart Hubs for Smart Ports in Smart Networks Anticipating the Massive introduction of Sensing, Computation, and Communication Technologies       Vacancies: No vacancies at this moment. Check back later. Inauguration Speech on communication, logistics, autonomous ships, and multi-machine engineering "What if ships could talk?", or: Coordination for Real-Time Logistics [Watch the public presentation online] Spotlight publication Supervisory nonlinear MPC for emergency voltage control using pattern search "The design of a higher-layer controller using model predictive control (MPC) is considered. The higher-layer controller uses MPC to determine set-points for controllers in a lower control layer. In this paper the use of an object-oriented model of the system for making predictions is proposed. When employing such an object-oriented prediction model the MPC problem is a nonlinear, non-smooth optimi..." [More...] R.R. Negenborn, S. Leirens, B. De Schutter, J. Hellendoorn. Supervisory nonlinear MPC for emergency voltage control using pattern search. Control Engineering Practice, vol. 17, no. 7, pp. 841-848, July 2009.    Publications: [Recent] [All] [In pictures] [Control & Coordination] [Transport Logistics] Recently added publications K. Wang, J. Li, X. Yan, L. Huang, X. Jiang, Y. Yuan, R. Ma, R.R. Negenborn. A novel bi-level distributed dynamic optimization method of ship fleets energy consumption. Accepted for publication in Ocean Engineering, 2019.    L. Wang, Q. Wu, J. Liu, S. Li, R.R. Negenborn. State-of-the-art research on motion control of maritime autonomous surface ships. Journal of Marine Science and Engineering, vol. 7, no. 12, December 2019. Open access..    S. Xie, V. Garofano, X. Chu, R.R. Negenborn. Model predictive ship collision avoidance based on Q-learning beetle swarm antenna search and neural networks. Ocean Engineering, vol. 193, no. 106609, December 2019.    S. Li, J. Liu, R.R. Negenborn, F. Ma. Optimizing the joint collision avoidance operations of multiple ships from an overall perspective. Ocean Engineering, vol. 191 (2019), no. 106511, 2019.    L. Chen, J.J. Hopman, R.R. Negenborn. Distributed model predictive control for cooperative floating object transport with multi-vessel systems. Ocean Engineering, vol. 191 (2019), no. 106515, 2019.    [More...] Infographics How will autonomous ships work? Books        Research in Sketches [More...] Active topic cloud (past 3 years) Keywords logistics, intermodal transport, container transport transport over water, control of ships transportation networks, inter-terminal transport water networks power networks, gas networks multi-agent systems, model predictive control, hybrid systems reinforcement learning, Kalman filters, learning robots The Brain of TU Delft Interreg 2 Seas: "ISHY: Implementation of Ship Hybridisation" A multi-machine engineering perspective H2020 EU.3.2.5 2017: Cross-cutting marine and maritime research: "Space@Sea -- Transport & Logistics" "Impulse Autonomous Shipping for Amsterdam 2018" SmartPort 2017 "Port Impact of Autonomous Ship Applications" NWO Social & Physical Sciences 2016 "Complexity Methods for Predictive Synchromodality" (COMET-PS) STW Perspectief 2015 Program "i-CAVE" Strategic Innovation Project AIDA: Automatic Identification of Research Trends STW Water 2015 Program "GasDrive" Topsector Water/STW Maritime 2013 Program "ShipDrive" Inter Terminal Transport at the Port of Rotterdam [More...]      Towards guaranteed port accessibility [More...] Innovational Research Incentives Scheme 2010 VENI Grant [More...] AIDA -- The Booklet Automatic Research Positioning & Trend Identification Journal Special Issues Computational Transport Logistics at Work (Special issue of Transportation Research Part E) Autonomous Ships (Special issue of SWZ Maritime 2017/02) Propulsion Systems (Special issue of SWZ Maritime 2015/10) Water Prediction and Control Technology (Special issue of Journal of Hydroinformatics) Videos on Inter Terminal Transport Opportunities for Real-Time Coordination Automated MTS and waterborne AGVs as solution?

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