Filetype
The methodology for production of biologics is going through a paradigm shift from batch-wise operation to continuous production. Lot of efforts are focused on integration, intensification, and continuous operation for decreased foot-print, material, equipment, and increased productivity and product quality. These integrated continuous processes with on-line analytics become complex processes, whi
Reliable six-degree-of-freedom pose estimation is a key requirement for autonomous on-orbit servicing (OOS), in which a robotic spacecraft performs tasks such as inspection, maintenance, and life extension of other satellites in orbit. However, generating trustworthy ground truth for algorithm development remains challenging. This thesis investigates calibration, sensor evaluation, and sensor fusi
This thesis concerns estimation in partially observed continuous and discrete time Markov models and focus on both inference about the conditional distribution of the unobserved process as well as parameter inference for the dynamics of the unobserved process. Paper A concerns calibration of advanced stock price models, in particular the Bates and NIG-CIR models, using options data observed th
This thesis presents methods for estimation and autonomous control of a hexacopter which is an unmanned aerial vehicle with six rotors. The hexacopter used is a ArduCopter 3DR Hexa B and the work follows a model-based approach using Matlab Simulink, running the model on a PandaBoard ES after automatic code generation. The main challenge will be to investigate how data from an Internal Measurement
Distributed multiple-input multiple-output (MIMO), also known as cell-free massive MIMO, emerges as a promising technology for sixth-generation (6G) systems to support uniform coverage and reliable communication. For the design and optimization of such systems, measurement-based investigations of real-world distributed MIMO channels are essential. In this paper, we present a sub-6 GHz indoor chann
The aim of this master thesis was to develop adaptive control for a quadrotor using Gaussian process regression (GP). Online regression with GPs can provide many benefits as it is a flexible non-linear regression model that can provide uncertainty measures of the estimate. However, online GP regression may also gives rise to problems. Because of the high numerical complexity of GPs, sparse approxi
Industrial control systems must ensure reliable operation while respecting physical and operational constraints. In practice, PID controllers dominate industrial control, often cited as covering over 95% of control loops. PID controllers are reliable, well understood, and easy to maintain, but they cannot explicitly handle constraints. In contrast, model predictive control (MPC) can enforce constr
Realistic Multiple-Input Multiple-Outout (MIMO) radio channel models are required in order to make fair system comparisons and to design proper signal processing algorithms using this technology. This technical report presents a full parameterization of the COST 2100 MIMO channel model for peer-to-peer communication in the 300 MHz band. Measurements were carried out in a semi-rural and suburban en
Industrial robots are fast and accurate when working with known objects at precise locations in well-structured manufacturing environments, as done in the classical automation setting. In one sense, limited use of sensors leaves robots blind and numb, unaware of what is happening in their surroundings. Whereas equipping a system with sensors has the potential to add new functionality and increase
Filtering and reconstruction of signals play a fundamental role in modern signal processing, telecommunications, and control theory and are used in numerous applications. The feedback principle is an important concept in control theory. Many different control strategies are based on the assumption that all internal states of the control object are available for feedback. In most cases, however, o
In recent years, there has been an increase of interest in smart grid concept, to adapt the power grid to improve the reliability, efficiency and economics of the electricity production and distribution. One of the generator side problem in this is to meet the power requirement while not wasting unnecessary power, thus keeping the cost down, which must be done while the frequency is kept in a suit
This thesis investigates the design and implementation of Model Predictive Control (MPC) and motion planning to enable an Unmanned Surface Vessel (USV) to perform autonomous escort missions. The objectives were to assess how the control architecture could utilize preexisting internal USV controllers and handle dynamic obstacles. Furthermore, how the controller architecture should be organized and
Digital controllers are traditionally implemented using periodic sampling, computation, and actuation events. As more control systems are implemented to share limited network and CPU bandwidth with other tasks, it is becoming increasingly attractive to use some form of event-based control instead, where precious events are used only when needed. Forms of event-based control have been used in prac
Mounting cameras on motorized objects has become possible in greater extent due to the emerging camera technology during the past few decades. This application could prove useful in several areas such as search and rescue operations, surveillance or even news monitoring. One hardship that this brings is the difficulty of keeping the camera unit stable while its setting is not. In the situations me
This study provides a comprehensive evaluation of eight high spatial resolution gridded precipitation products in Adige Basin located in Italy within 45–47.1°N. The Adige Basin is characterized by a complex topography, and independent ground data are available from a network of 101 rain gauges during 2000–2010. The eight products include the Version 7 TRMM (Tropical Rainfall Measuring Mission) Mul
Monitoring crop growth and estimating crop yield are essential for managing agricultural production, ensuring food security, and maintaining sustainable agricultural development. Combining the mechanistic framework of a crop growth model with remote sensing observations can provide a means of generating realistic and spatially detailed crop growth information that can facilitate accurate crop yiel
We present a novel high-resolution inverse modelling system ("FLEXVAR") based on FLEXPARTCOSMO back trajectories driven by COSMO meteorological fields at 7 km×7 km resolution over the European COSMO-7 domain and the four-dimensional variational (4DVAR) data assimilation technique. FLEXVAR is coupled offline with the global inverse modelling system TM5-4DVAR to provide background mole fractions ("b
Anticipatory and predictive models are becoming very important features of robot systems. This thesis investigates some aspects of predictive modeling. Is prediction always a good thing? How important is it to anticipate what will happen in the future? Is it better to anticipate far into the future or to focus on the next few seconds? What are the requirements for predictive models? Predictive mod
