Wind Classification using Unsupervised Learning: In support of the Olympic Sailing Competition in Tokyo, Japan

During the preparation for the Olympic Sailing Competition, held in 2021 in Tokyo, Japan, the Dutch National Sailing Team encountered days with unpredicted wind behaviour. To gain more understanding in the wind patterns occurring, a deep learning based approach is taken. The goal of this research is to find out if unsupervised learning methods...

Meta-heuristic improvement of order picking efficiency: Exploiting cross-order similarity in a goods-to-person warehouse

This research aims at determining a suitable order release strategy for a warehouse featuring a shuttle-based storage and retrieval system with multiple goods-to-person picking workstations. These picking workstations facilitate efficient picking; however, current release strategies do not take similarity between orders into account, while this...

Dynamic modelling and control of a solid oxide reversible cell for power disturbance rejection in a mixed power grid

The integration of variable renewable energy sources (RESs) in the electrical power grid leads to larger and faster variations in the power demanded from controllable power sources. This is a problem, because flexibility of (base load) power plants is limited. Solid oxide reversible cells(SORCs) can be used as load-shifting devices to reduce...

Using Mechanical System Dynamics toModel Time-Discounting in Behavioural Economics

Time-discounting in behavioural economics is modelled using mechanical system dynamics through the economic engineering framework. The economic engineering framework is being developed at the Delft Center for Systems and Control, and uses mechanical system dynamics to model economic processes and systems. Time-discounting is the calculation of...

Optimal control of combined chemo-radiation therapy treatments for improving cancer care

Combined chemo-radiation treatments are often used to enhance tumor cell kill, with respect to their separate treatments. Currently, chemo-radiation therapy treatments are prescribed as a separately optimized radiotherapy treatment with the addition of a generic chemotherapy regimen. The dosing of the combined therapies is mostly based on...

Online Reinforcement Learning Control of an Electromagnetic Manipulator

Machine Learning Control is a control paradigm that applies Artificial Intelligence methods to control problems. Within this domain, the field of Reinforcement Learning (RL) is particularly promising, since it provides a framework in which a control policy does not have to be programmed explicitly, but can be learned by an intelligent controller...

Control Strategies for Grasping and Holding Deformable Items Using a Gripper on a Robotic Arm

Because of the increasing e-commerce volume, resulting in increasing demands on the speed of delivery, logistical processes become more and more automated. Order picking is one of the last tasks that is done by humans in warehouses, because humans are flexible with respect to the large variability and changeability in items. However, it is a...

Radial basis functions for aberration retrieval in adaptive optics

The use of radial basis function (RBF) expansion as a means to represent the generalized pupil function for aberration retrieval from intensity point-spread function has been investigated in this research article. The optimal choice of RBF hyper-parameters is derived empirically to achieve an increased accuracy of approximation along with well...

Hybrid Adaptive Integrated Chassis Control: vehicle lateral stability in presence of uncertainty

Extensive advancements in the field of mobility and safety in transportation in last few decades<br/>have acted as a catalyst for the expansion of automobile industry. The research for the evolution<br/>of new technologies, vehicle safety regulations and specifications and the market requirements<br/>has given this progress a greater push. The...