Publications       Rudy Negenborn
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Adaptive control for autonomous ships with uncertain model and unknown propeller dynamics


"Motion control is one of the most critical aspects in the design of autonomousships. During maneuvering, the dynamics of propellers as well as the craft hy-drodynamical specifications experience sever uncertainties. In this paper, anadaptive control approach is proposed to control the motion and trajectorytracking of an autonomous vessel by adopting neural networks that is used f..." [More...]

Adaptive control for autonomous ships with uncertain model and unknown propeller dynamics. A. Haseltalab, R.R. Negenborn. Control Engineering Practice, vol. 91, no. 104116, October 2019.   


Impact and relevance of transit disturbances on planning in intermodal container networks


"In North-West Europe, the options for intermodal inland transportation of containers are increasing. Inland corridors become increasingly interconnected in hinterland networks. To minimize operating costs, new methods are required that allow integral network operations management. The network operations consist of allocating containers to available inland transportation services, i.e. planning. Fo..." [More...]

Impact and relevance of transit disturbances on planning in intermodal container networks. B. van Riessen, R.R. Negenborn, G. Lodewijks, R. Dekker. Maritime Economics & Logistics, vol. 17, pp. 440-463, December 2015.   


Closed-loop scheduling and control of waterborne AGVs for energy-efficient Inter Terminal Transport


"We propose closed-loop energy-efficient scheduling and control of an autonomous Inter Terminal Transport (ITT) system using waterborne Autonomous Guided Vessels (waterborne AGVs). A novel pick-up and delivery problem considering safe intervals between berthing time slots of different waterborne AGVs is proposed. Waterborne AGVs are controlled in a cooperative distributed way to carry out assigned ..." [More...]

Closed-loop scheduling and control of waterborne AGVs for energy-efficient Inter Terminal Transport. H. Zheng, R.R. Negenborn, G. Lodewijks. Transportation Research Part E: Logistics and Transportation Review, vol. 105, pp. 261-278, September 2017.   


Synchromodal freight transport re-planning under service time uncertainty: An online model-assisted reinforcement learning


"The objective of this study is to address the issue of service time uncertainty in synchromodal freight transport, which can cause delays, inefficiencies, and reduced satisfaction for shippers. The proposed solution is an online deep Reinforcement Learning (RL) approach that takes into account the service time uncertainty, assisted by an Adaptive Large Neighborhood Search (ALNS) heuristic that pro..." [More...]

Synchromodal freight transport re-planning under service time uncertainty: An online model-assisted reinforcement learning. Y. Zhang, R.R. Negenborn, B. Atasoy. Transportation Research Part C: Emerging Technologies, vol. 156, no. 104355, November 2023. Open access.   


Adaptive control for autonomous ships with uncertain model and unknown propeller dynamics


"Motion control is one of the most critical aspects in the design of autonomousships. During maneuvering, the dynamics of propellers as well as the craft hy-drodynamical specifications experience sever uncertainties. In this paper, anadaptive control approach is proposed to control the motion and trajectorytracking of an autonomous vessel by adopting neural networks that is used f..." [More...]

Adaptive control for autonomous ships with uncertain model and unknown propeller dynamics. A. Haseltalab, R.R. Negenborn. Control Engineering Practice, vol. 91, no. 104116, October 2019.   


Synchromodal freight transport re-planning under service time uncertainty: An online model-assisted reinforcement learning


"The objective of this study is to address the issue of service time uncertainty in synchromodal freight transport, which can cause delays, inefficiencies, and reduced satisfaction for shippers. The proposed solution is an online deep Reinforcement Learning (RL) approach that takes into account the service time uncertainty, assisted by an Adaptive Large Neighborhood Search (ALNS) heuristic that pro..." [More...]

Synchromodal freight transport re-planning under service time uncertainty: An online model-assisted reinforcement learning. Y. Zhang, R.R. Negenborn, B. Atasoy. Transportation Research Part C: Emerging Technologies, vol. 156, no. 104355, November 2023. Open access.   


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