Frequency-Domain Modelling of Reset Control Systems using an Impulsive Description

The ever-increasing industry desire for improved performance makes linear controller design run into its fundamental limitations. A nonlinear controller, such as Reset Control (RC), is needed to overcome these. RC is promising since, unlike other nonlinear methods, it easily integrates into the PID design framework preferred by industry. Thus...

Data-Driven Filtering for Large-Scale Adaptive Optics

The visualization of objects within or beyond a turbulent medium is hampered by the aberrations the medium induces in the wavefront. The sharpness of an image is maximal when the incoming wavefront is flat, with aberrated wavefronts yielding distorted images of limited utility. In the particular case of astronomy, the flat wavefront of the light...

Exploration and Coverage: A Deep Reinforcement Learning Approach

This work addresses the problem of exploration and coverage using visual inputs. Exploration and coverage is a fundamental problem in mobile robotics, the goal of which is to explore an unknown environment in order to gain vital information. Some of the diverse scenarios and applications in which exploratory robots can have a significant impact...

Development of a Detection and Tracking of Moving Vehicles system for 2D LIDAR sensors

The main objective of this thesis was the development and evaluation of a Detection and Tracking of Moving Objects (DATMO) system, that is capable of reliably tracking nearby vehicles from a moving car. The developed system takes in raw 2D LIght Detection And Ranging (LIDAR) measurements as input and detects objects of interest by clustering...

Iterative Bias Estimation for an Ultra-Wideband Localization System

Three bias estimation frameworks are presented that mitigate position-dependent ranging errors often present in ultra-wideband localization systems. State estimation and control are integrated, such that the positioning accuracy improves over iterations. The frameworks are experimentally evaluated on a quadcopter platform. Two state augmentation...

Data-Driven Techniques for Printer Prognosis and Performance Improvement: Design and Critical Comparison

It is of key importance for modern printing systems to maintain high standards of efficiency, reliability and print quality. In this regard, the scope of this work is to investigate the applicability of data analysis and machine learning techniques to improve the performances of industrial printers manufactured at Océ Technologies. Two critical...

Fetal cardiovascular simulations to assess the feasibility of intrauterine ECMO

The placenta is very important during the start of life, providing the fetus with oxygen and nutrients from the maternal blood. Impaired growth of the placenta and additional placental ischaemia endangers the exchange of gasses, exchange of nutrients, and optimal growth of the fetus. This thesis investigates the feasibility of intrauterine ECMO...

Active inference for adaptive and fault tolerant control: An application to robot manipulators

Dealing with inherently unmodeled dynamics and large parameter variations or faults, is a challenging task while controlling robot manipulators. Classical control techniques cannot usually provide satisfactory responses, and often external supervision systems have to be designed to handle the faults. Recent research has shown that active...

Deep End-to-end Network for 3D Object Detection in the Context of Autonomous Driving

Nowadays, autonomous driving is a trending topic in the automotive field. One of the most crucial challenges of autonomous driving research is environment perception. Currently, many techniques achieve satisfactory performance in 2D object detection using camera images. Nevertheless, such 2D object detection might be not sufficient for autonomous...

Comparison of time-varying system identification methods to assess joint impedance

Joint impedance describes the dynamic resistance of a joint in response to position perturbations. Joint impedance is known to vary nonlinearly during movement caused by varying joint angle and muscle activation. The nonlinear behaviour can be described using linear time-varying models under certain assumption. Recently a number of time-varying...