Filtyp
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
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
We have previously proposed a blind system identification method that exploits the underlying dynamics of non-Gaussian signals in [Li and Andersen, "Blind identification of Non-Gaussian Autoregressive Models for Efficient Analysis of Speech Signals," Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2006, vol. 1, pp. I-1205-1-1208]. The signal mod
Two main topics are considered in this thesis: Machining with industrial robot manipulators and optimal motion control of robots and vehicles. The motivation for research on the first subject is the need for flexible and accurate production processes employing industrial robots as their main component. The challenge to overcome here is to achieve high-accuracy machining solutions, in spite of the
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
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
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
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
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
It is tractable to increase the torque for an HCCI engine and one way is to add a turbocharger. Operating in HCCI mode requires accurate control of the combustion phasing, CA50. The higher the engine torque, the narrower the CA50 window becomes where HCCI operation is maintained. As the CA50 varies stochastically between cycles this requires improved CA50 control for turbo HCCI engines. The main f
Personalized patient care has gained increasing attention in recent years. Precise drug dosing is critical for patient safety and good clinical outcomes, especially in intensive care units, where patients often are in critical conditions. Such treatments can include stabilizing blood pressure and heart rate or maintaining safe anesthesia levels. However, the inter-patient variability in the drug r
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
In this paper, a virtual sensor for the estimation of the injected pilot mass in-cycle is proposed. The method provides an early estimation of the pilot mass before its combustion is finished. Furthermore, the virtual sensor can also estimate pilot masses when its combustion is incomplete. The pilot mass estimation is conducted by comparing the calculated heat release from in-cylinder pressure mea
Professor Kontaktinformation E-post: jonas [dot] ardo [at] mgeo [dot] lu [dot] se Telefon: +46 46 222 40 31 Mobil: +46 72 202 50 28Organisation Miljö- och geovetenskapliga institutionen (MGeo) Besöksadress: 449 Hämtställe: 16 WebbplatsJonas Ardös profil i Lunds universitets forskningsportalAndra roller Medlem i Strategiskt forskningsområde BECC: Biodiversity and Ecosystem services in a Changing Cl
https://www.nateko.lu.se/sv/jonas-ardo - 2026-10-04
