The effect of kite control unit mass and drag on the flight behavior of an airborne wind energy system kite

Airborne wind energy (AWE) is an emerging field that aims to revolutionize the wind energy sector.This work focuses on the aspects of modeling AWE kite flight behavior. Research on such modelsis important since new or improved models can potentially reduce development time and costs andprovide insight in the role of key system parameters.This...

The State Space Formulation of Active Inference: Towards Brain-Inspired Robot Control

This thesis provides an exposition of the theory of Active Inference in a control theoretic context. Active Inference is a remarkably powerful neuroscientific theory that unifies many characteristics of the biological brain. As such, Active Inference provides a valid inspiration in search of improvements in bio-inspired robot control algorithms....

State Estimation for Nanosatellite-Class Reaction Wheels

In this MSc. thesis, state estimation for a nanosatellite-class reaction wheel has been investigated. Two LPV observers, using different sensor information, have been synthesized. The performance of the designed observers has been evaluated using a detailed simulation of the reaction wheel (including disturbances that occur during the reaction...

A Predictive Energy Management Strategy for Plug-in Hybrid Electric Vehicles utilizing Route Preview

A Plug-in Hybrid Electric Vehicle (PHEV) can achieve a considerably higher overall fuel economy than conventional vehicles. The fuel economy of PHEVs however, strongly depends on the supervisory control strategy of the hybrid powertrain. Compared to conventional, non-predictive, supervisory control systems, predictive control methods can further...

Lane Change Path Planning: with State-Dependent Safety Constraints

In the past years a number of SAE level 2 driving automation systems have come available in commercial vehicles. An example is Volvo's Pilot Assist, which provides a more comfortable journey for the driver as certain parts of the dynamic driving task are taken away, but it still requires the driver to be attentive in order to supervise the...

Automated malaria diagnosis using convolutional neural networks in an on-field setting: The analysis of low quality smartphone based microscope images

This study focuses on automated malaria diagnosis in low quality blood smear images, captured by a low-cost smartphone based microscope system. The aim is to localize and classify the healthy and infected erythrocytes (red blood cells) in order to evaluate the parasitaemia in an infected blood smear. Due to the lower quality of the smartphone...