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
Massive introduction of
Sensing, Computation, and Communication Technologies
1 PhD position, 2 post-doc postions, 1 tenure track faculty position Vacancies:
Efficient multi-scenario model predictive control for water resources management with ensemble streamflow forecasts
"Model Predictive Control (MPC) is one of the most advanced real-time control techniques that has been widely applied to water resources management (WRM). MPC can manage the water system in a holistic manner and has a flexible structure to incorporate specific elements, such as setpoints and constraints. Therefore, MPC has shown its versatile performance in many branches of WRM. Nonetheless, with t..." [ More...] X. Tian, R.R. Negenborn, P.J. van Overloop, J.M. Maestre, A. Sadowska, N. van de Giesen. Efficient multi-scenario model predictive control for water resources management with ensemble streamflow forecasts. Advances in Water Resources, vol. 109, pp. 58-68, 2017.
[ Publications: Recent]
[ In pictures]
[ Control & Coordination]
[ Transport Logistics]
Recently added publications
T. Jonker, M.B. Duinkerken, N. Yorke-Smith, A. de Waal, R.R. Negenborn. Coordinated optimization of equipment operations in a container terminal. Accepted for publication in Flexible Services and Manufacturing, 2019. L. Chen, Y. Huang, H. Zheng, J.J. Hopman, R.R. Negenborn. Cooperative multi-vessel systems
in urban waterway networks. Accepted for publication in IEEE Transactions on Intelligent Transportation Systems, 2019. A. Haseltalab, M. Ayala Botto, R.R. Negenborn. Model predictive DC voltage control for all-electric ships. Control Engineering Practice, vol. 90, pp. 133-147, September 2019. D. Souravlias, M. B. Duinkerken, S. Morshuis, D.L. Schott, R.R. Negenborn. Stochastic floating quay crane scheduling on offshore platforms: a simheuristic approach. Accepted for the 2019 International Conference on Harbor, Maritime and Multimodal Logistic Modelling and Simulation (HMS'19), Lisbon, Portugal, September 2019. C. Liu, H. Zheng, R.R. Negenborn, X. Chu, S. Xie. Adaptive predictive path following control based on least squares support vector machines for underactuated autonomous vessels
. Accepted for publication in Asian Journal of Control, 2019.
How will autonomous ships work?
Research in Sketches
Active topic cloud (past 3 years)
transport over water,
control of ships
transportation networks, inter-terminal transport
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"
"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
Inter Terminal Transport at the Port of Rotterdam
Towards guaranteed port accessibility
Innovational Research Incentives
Scheme 2010 VENI
AIDA -- The Booklet
Automatic Research Positioning & Trend Identification
Journal Special Issues
Computational Transport Logistics at Work
(Special issue of Transportation Research Part E)
(Special issue of SWZ Maritime 2017/02)
(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?