Exploiting high altitude wind energy using power kites is an emerging topic in the field of renewable energy. The claimed advantages of power kites over traditional wind power technologies are the lower construction costs, less land occupation and more importantly, the possibility of efficiently harvesting wind energy at high altitudes, where more dense and steady wind power exists. One of the most challenging issues to bring the power kite concept to real industrialization is the controller design. While traditional wind turbines can be inherently stabilized, the airborne nature of kites causes a strong instability of the systems. This thesis aims to develop a novel economic model predictive path-following control (EMPFC) framework to tackle the path-following control of power kites, as well as provide insightful stability analysis of the proposed control scheme. Chapter 3 is focused on the stability analysis of EMPFC. We proceed with a sampled-data EMPC scheme for set-point stabilization problems. An extended definition of dissipativity is introduced for continuous-time systems, followed by giving sufficient stability conditions. Then, the EMPFC scheme for output path-following problems is proposed. Sufficient conditions that guarantee the convergence of the system to the optimal operation on the reference path are derived. Finally, an example of a 2-DoF robot is given. The simulation results show that under the proposed EMPFC scheme, the robot can follow along the reference path in forward direction with enhanced economic performance, and finally converges to its optimal steady state. In Chapter 4, the proposed EMPFC scheme is applied to a challenging nonlinear kite model. By introducing additional degrees of freedom in the zero-error manifold (i.e., the space where the output error is zero), a relaxation of the optimal operation is achieved. The effectiveness of the proposed control scheme is shown in two aspects. For a static reference path, the generated power is increased while the kite is stabilized in the neighborhood of the reference path. For a dynamic reference path, the economic performance can be further enhanced since parameters for the reference path are treated as additional optimization variables. The proposed EMPFC achieves the integration of path optimization and path-following, resulting in a better economic performance for the closed-loop system. Simulation results are given to show the effectiveness of the proposed control scheme. Finally, Chapter 5 concludes the thesis and future research topics are discussed. / Graduate / 2020-05-14

Water is a major factor limiting cotton production and farmers must aim to optimise crop water use through timely irrigation scheduling decisions. Airborne video imagery when calibrated with a low density of ground based observations, offers the potential for near real time monitoring of crop condition, through sequential coverages of entire cotton fields. Using commercially available video equipment mounted on a light aircraft images were acquired of field experiments that were established in commercial cotton fields to test if the imagery could monitor changes in crop condition. Ground data collected from these experiments were used to evaluate green, red, near infrared and thermal band imagery for irrigated crop management. Prior to acquiring imagery, a ground radiometer study was conducted to investigate if canopy reflectance changed with the onset of crop water stress. Canopy reflectance decreased in the near infrared and green bands during the five day period prior to the crop's normal irrigation date. Red reflectance increased only after the crop irrigation was due, when the crop was suffering from water stress. The greatest change in canopy reflectance was in the near infrared region, attributable in part to a decrease in ground cover caused by canopy architectural changes including leaf wilting. The results of this experiment were used to select spectral filters for the video cameras. A range of crop conditions were identified in the imagery including; crop waterlogging, wheeltrack soil compaction, crop nitrogen status, different varieties, crop maturity, canopy development, soil moisture status, cotton yield and nutgrass weeds. Thermal imagery was the most successful for distinguishing differences in the crop soil moisture status. Near infrared imagery was most closely related to crop canopy development and is recommended for monitoring crop growth. Linear relationships were found between spectral responses in the imagery, crop reflectance (%) and crop temperature measured on the ground. Near infrared reflectance linearly increased, while spectral responses in the green, red and thermal bands exhibited an inverse relationship with plant height and ground cover. Imagery collected early in the season was affected by the soil background. Final lint yield was related to imagery in the red band. As the soil moisture level declined, crop temperature increased while reflectance in the green band decreased. To ensure an accurate relationship between soil moisture and thermal imagery, separate calibration equations are recommended for different stages in the season. Green, red and near infrared imagery were affected by the sun angle that caused one side of the imagery to appear brighter than the other. This problem was greatest in the green and red bands, but was not evident in the thermal imagery. Changes in solar radiation and air temperature on some occasions caused greater variation to the imagery between flights, than changes in crop condition per se. Therefore, it is not aIways possible to directly determine the soil moisture status from canopy temperature. Further research is required to correct imagery for environmental variables such as solar radiation, air temperature and vapour pressure deficit. Thermal imagery offers many improvements to current irrigation scheduling techniques including the facilitation of locating more representative ground sampling points. Thermal imagery also enables cotton fields on a farm to be ranked according to their soil moisture status. This then provides farmers with a visual picture of the crop water status across the whole farm, which is not possible using conventional ground scheduling techniques. At this stage, airborne video imagery will not replace soil moisture data collected for irrigation scheduling, however offers potential to enhance irrigation scheduling methods by addressing the problem of crop variability within cotton fields.

I address the geometric problem of the pendulum-like swinging of towed birds for AEM platforms. I establish a link between actual observed bird swing and its effect on survey data for two different systems and explain the link by a model that compares actual survey data to the calculated mutual inductance coupling of a dipole pair over an infinitely conductive half space, which pair is permitted arbitrary pitch, roll and altitude changes. I develop a non-linear filter that removes bird swing effects from survey data which successfully corrected data from 3 different AEM surveys. Calibration of several different time domain AEM systems is attempted using an accurately laid out and surveyed, closed, multi-turn loop of known resistance and self-inductance that is placed on - but insulated from - resistive ground. I derive a rigourous mathematical model that predicts airborne receiver's response to the coupling to the transmitter current waveform and total system geometry. The method was proven to be successful over resistive ground, with significant system problems identified such as: altimetry error, spatial averaging of data during postprocessing, error in the predicted horizontal position of the AEM platform, receiver windowing and timing errors and bird swing. I show that, although we can calibrate a time domain AEM system for a single flyover, it is impossible to calibrate an AEM system for geometry. As an intermediate step in the calibration process, I show that by monitoring the current induced in the ground loop we can obtain the waveform of the AEM transmitter current throu gh deconvolution in the Fourier domain. Simple and cost effective methods for the improvement of quantitative AEM data are presented in this thesis. However, until the geometry problem of AEM platforms is solved, full system calibration will not be obtained and filters will need to be applied to the data. I recommend the use of: GPS antennas mounted on all towed birds, able to be post-processed for accurate position recovery, reliable bird-mounted scanning altimeters that do not rely on range-finding technology but instead employ a shortest path algorithm, pitch and roll sensors mounted on the trailed bird and the measurement of airspeed of both the towed bird and the aircraft during surveys.

During several years research has been performed at the Department of Laser Systems, the Swedish Defense Research Agency (FOI), to develop methods to produce high resolution 3D environment models based on data acquired with airborne laser systems. The 3D models are used for several purposes, both military and civilian applications, for example mission planning, crisis management analysis and planning of infrastructure. We have implemented a new format to store laser point data. Instead of storing rasterized images of the data this new format stores the original location of each point. We have also implemented a new method to detect outliers, methods to estimate the ground surface and also to divide the remaining data into two classes: buildings and vegetation. It is also shown that it is possible to get more accurate results by analyzing the points directly instead of only using rasterized images and image processing algorithms. We show that these methods can be implemented without increasing the computational complexity.

<p>Spatial variability of the Earth's surface has a considerable impact on the atmosphere at all scales and understanding the mechanisms involved in land-atmosphere interactions is hindered by the scarcity of appropriate observations. A measurement gap exists between traditional point sensors and large aircraft and satellite-based sensors in collecting measurements of atmospheric quantities. Point sensors are capable of making long time series of measurements, but cannot make measurements of spatial variability. Large aircraft and satellites make measurements over large spatial areas, but with poor spatial and temporal resolution. A helicopter-based platform can make measurements on scales relevant for towers, especially close to the Earth's surface, and can extend these measurements to account for spatial variability. Thus, the Duke University Helicopter Observation Platform (HOP) is designed to fill the existing measurement gap. </p><p>Because measurements must be made in such a way that they are as uncontaminated by the platform itself as much as is possible, it is necessary to quantify the aerodynamic envelope of the HOP. The results of an analytical analysis of the location of the main rotor wake at various airspeeds are shown. Similarly, the results of a numerical analysis using the commercial Computational Fluid Dynamics software Fluent are shown. The optimal flight speed for the sampling of turbulent fluxes is found to be around 30 m/s. At this airspeed, the sensors located in front of the nose of the HOP are in advance of the wake generated by the main rotor. This airspeed is also low enough that the region of high pressure due to the stagnation point on the nose of the HOP does not protrude far enough forward to affect the sensors. Measurements of differential pressures, variables and turbulent fluxes made while flying the HOP at different airspeeds support these results. No systematic effects of the platform are seen at airspeeds above about 10 m/s.</p><p>Processing of HOP data collected using the current set of sensors is discussed, including the novel use of the Empirical Mode Decomposition (EMD) to detrend and filter the data. The EMD separates the data into a finite number of Impirical Mode Functions (IMFs), each of which is unique and orthogonal. The basis is determined by the data itself, so that it need not be known a priori, and it is adaptive. The EMD is shown to be an ideal tool for the filtering and detrending of HOP data using data gathered during the Cloud and Land Surface Interaction Campaign (CLASIC). </p><p>The ability of the HOP to accurately measure atmospheric profiles of potential temperature is demonstrated. During experiments conducted in the marine boundary layer (MBL) and the convective boundary layer (CBL), HOP profiles are evaluated using profiles from an elastic backscatter lidar. The HOP and the lidar agree on the height of the boundary layer in both cases, and the HOP effectively locates other atmospheric structures.</p><p>Atmospheric sensible and latent heat fluxes, turbulence kinetic energy (TKE) and horizontal momentum fluxes are also measured, and the resulting information is used to provide context to tower-based data collected concurrently. A brief comparison made over homogeneous ocean conditions yields good results. A more exhaustive evaluation is made using short HOP flights made over an orchard during the Canopy Horizontal Turbulence Study (CHATS).</p> / Dissertation

This study presents airborne measurements of HO2NO2, HCl and SO2 using chemical ionization mass spectrometry (CIMS) during the Intercontinental Chemical Transport Experiment (INTEX) field campaign, an intensive study to characterize the chemical composition of the troposphere in the eastern United States, Mexico City, and the North Pacific which is the outflow region of Asia. The first direct in situ measurements of HO2NO2 were made in the free troposphere over the eastern U.S. during summer 2004. The highest mean mixing ratio of 76 pptv (median = 77 pptv, = 39 pptv) was observed in the altitude range of 8-9 km. Highly constrained steady state calculations of HO2NO2 using measured HOx levels are poorly correlated with observed HO2NO2 in the upper troposphere (8 km < z < 12 km; the median ratio of [HO2NO2]SS-MEA/[HO2NO2]MEA = 2.9). However, steady state HO2NO2 using model-derived HOx shows reasonable agreement with measurements in the free troposphere ([HO2NO2]SS-MEA/[HO2NO2]MEA = 1.3). The vertical distribution of HCl was measured over the north Pacific during May 2006 from the marine boundary layer (MBL) up to lower stratosphere. Recent stratospheric influence in the upper troposphere (8 km < z < 12 km) was efficiently identified from enhanced HCl (up to ~100 pptv) relative to very low background levels (< 2pptv). In the remote MBL, the acidification of seasalt aerosols by HNO3 appeared to be the major source of HCl, with level consistently over 20 pptv (up to 400 pptv). The distribution of SO2 was measured in the outflow region of the eastern U.S. and Asia; two major anthropogenic SO2 source regions. This study presents vertical and horizontal distributions of SO2 and relevant gas phase and aerosol parameters to characterize SO2 transport in the troposphere. SO2 in the boundary layer was efficiently transported to the upper troposphere by deep convection and frontal uplift processes. High SO2 in convective plume in the upper troposphere were strongly correlated with ultrafine aerosols.Conversely, SO2 from frontal uplift shows a strong correlation with non-volatile aerosols. Comparisons of SO2 products from global 3-D chemical transportation models (GEOS-CHEM and MOZART) with observations suggest that sulfur sources are relatively well described but that the oxidation mechanism needs refinement.

Burning joss paper and incense is a significant Taoist ceremonial practice in Asian countries such as Taiwan and China. The burning of joss paper has been demonstrated to significantly create particulate matters (PM) and to cause air pollution problems. PM in the atmosphere is among the primary air pollutants, and their sources are factories, vehicles, construction fields, combustion, vehicle exhaust dust, and aerosols derived from photochemical reactions. Numerous sources of environmental PM exist. Thus, the ability to rapidly determine the particulate type and source to adjust the controls and develop policies is an important issue for air quality management. This dissertation consists of two parts on the particulate emission control and characteristic identification. In the first part, we study investigates feasible options of air pollution control devices (APCD) for joss paper furnaces in temples, and used a 40 kg/hr joss paper furnace for testing. This paper examined particulate removal efficiencies of two options: a bag house (capacity 30 m3/min at 108 ¢J) and a wet scrubber (capacity 40 m3/min at 150 ¢J). The results indicate that PM in the diluted flue gas at the bag-house inlet were 76.6 ¡Ó 32.7 mg/Nm3 (average ¡Ó standard deviation), and those at the outlet of the bag-house could be reduced to as low as 0.55 ¡Ó 1.28 mg/Nm3. An average PM removal efficiency of 99.3 % could be obtained with a filtration speed of approximately 2.0 m/min evaluated at 108 ¢J. The wet scrubber removed approximately 70 % of PM, with scrubbing intensities higher than 4.0 L/m2.s across the scrubber cross-section. For the duration of the experiment, no visual white smoke (water mist) was observed at the exit of the wet scrubber with a combustion rate of 16 kg/hr of joss paper, and the scrubbing water temperature was automatically sustained at lower than 61 ¢J. The study concluded that both bag filtration and wet scrubbing are suitable techniques to control particulate emission from joss paper furnaces in Taiwanese temples. The bag filtration technique, while achieving higher efficiencies than the wet scrubbing technique, requires more space and cost. Examinations of bottom and fly ashes of combusted joss paper with X-ray diffraction (XRD) revealed the presence of calcium oxide in the fly ash, while certain metals were found in the bottom ash. The second part aimed at the investigates surface characteristics of airborne PM sampled from air pollution control devices of a number of industrial operations. The PM sources selected for this study comprise the following operations or processes: a coke oven, iron ore sintering furnace, blast furnace, and basic oxygen furnace from an integrated steelmaking plant; electric arc furnaces of two secondary steelmaking plants; a municipal solids waste incinerator; two oil-fired boilers; and a coal-fired power plant boiler. The collected PM samples were analyzed using a scanning electronic microscope (SEM) and energy-dispersive X-ray spectroscope (EDS) to determine their chemical composition and surface characteristics. Results for each PM sample regarding size, surface characteristics, and chemical compositions can be used to trace the related emission industrial sources.

LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatiallyexplicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for realtime remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real- time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real- time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for realtime forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of airborne scanning or profiling laser systems for remotely measuring various forest structural attributes at a range of scales, i.e., from individual tree, plot, stand and up to regional levels. The system not only provides a regional assessment tool, one that can be used to repeatedly, remotely measure hundreds or thousands of square kilometers with little/no analyst interaction or interpretation, but also serves as a paradigm for future efforts in building more advanced airborne laser systems such as real-time laser scanners.

In this study, the performances of the optical sensors and instruments carried on both ground-based and airborne platforms were evaluated for monitoring crop growing status, detecting the vegetation response to aerial applied herbicides, and identifying crop nitrogen status. Geostatistical analysis on remotely sensed data was conducted to investigate spatial structure of crop canopy normalized difference vegetation index and multispectral imagery. A computerized crop monitoring system was developed that combined sensors and instruments that measured crop structure and spectral data with a global positioning system. The integrated crop monitoring system was able to collect real-time, multi-source, multi-form, and crop related data simultaneously as the tractor-mounted system moved through the field. This study firstly used remotely sensed data to evaluate glyphosate efficacy on weeds applied with conventional and emerging aerial spray nozzles. A weedy field was In this study, the performances of the optical sensors and instruments carried on both ground-based and airborne platforms were evaluated for monitoring crop growing status, detecting the vegetation response to aerial applied herbicides, and identifying crop nitrogen status. Geostatistical analysis on remotely sensed data was conducted to investigate spatial structure of crop canopy normalized difference vegetation index and multispectral imagery. A computerized crop monitoring system was developed that combined sensors and instruments that measured crop structure and spectral data with a global positioning system. The integrated crop monitoring system was able to collect real-time, multi-source, multi-form, and crop related data simultaneously as the tractor-mounted system moved through the field. This study firstly used remotely sensed data to evaluate glyphosate efficacy on weeds applied with conventional and emerging aerial spray nozzles. A weedy field was set up in three blocks and four aerial spray technology treatments were tested. Spectral reflectance measurements were taken using ground-based sensors from all the plots at 1, 8, and 17 days after treatment. The results indicated that the differences among the treatments could be detected with spectral data. This study could provide applicators with guidance equipment configurations that can result in herbicide savings and optimized applications in other crops. The main focus of this research was to apply sensor fusion technology to ground-based and airborne imagery data. Experimental plots cropped with cotton and soybean plants were set up with different nitrogen application rates. The multispectral imagery was acquired by an airborne imaging system over crop field; at the same period, leaf chlorophyll content and spectral reflectance measurements were gathered with chlorophyll meter and spectroradiometer at canopy level on the ground, respectively. Statistical analyses were applied on the data from individual sensor for discrimination with respect to the nitrogen treatment levels. Multisensor data fusion was performed at data level. The results showed that the data fusion of airborne imagery with ground-based data were capable of improving the performance of remote sensing data on detection of crop nitrogen status. The method may be extended to other types of data, and data fusion can be performed at feature or decision level.

<p>In recent years the aviation industry is moving towards the use of programmable logic devices in airborne safety critical systems. To be able to certify the close to fail-safe functionality of these programmable devises (e.g. FPGAs) to the aviation authorities, the aviation industry uses a guideline for design assurance for airborne electronic hardware named RTCA DO-254. At the same time the PLD industry is developing ever more complex embedded system-on-chip solutions integrating more and more functionality on a single chip.</p><p>This thesis looks at the problems that rise when trying to certify system-on-chip solutions according to RTCA DO-254. Used as an example of an embedded FPGA, the Actel Fusion FPGA chip with integrated analog and digital functionality will be tested according to the verification guidance. The results show that for the time being, the examined embedded system-on-chip FPGAs can not be verified to be used in airborne safety critical systems.</p>