This dissertation describes the development of a requirements analysis methodology that takes into account the concept of operations and the hierarchical decomposition of aerospace systems. At the core of the methodology, the Analytic Network Process (ANP) is used to ensure the traceability between the qualitative and quantitative information present in the hierarchical model. The proposed methodology is implemented to the requirements definition of a hurricane tracker Unmanned Aerial Vehicle. Three research objectives are identified in this work; (1) improve the requirements mapping process by matching the stakeholder expectations with the concept of operations, systems and available resources; (2) reduce the epistemic uncertainty surrounding the requirements and requirements mapping; and (3) improve the requirements down-selection process by taking into account the level of importance of the criteria and the available resources. Several challenges are associated with the identification and definition of requirements. The complexity of the system implies that a large number of requirements are needed to define the systems. These requirements are defined early in the conceptual design, where the level of knowledge is relatively low and the level of uncertainty is large. The proposed methodology intends to increase the level of knowledge and reduce the level of uncertainty by guiding the design team through a structured process. To address these challenges, a new methodology is created to flow-down the requirements from the stakeholder expectations to the systems alternatives. A taxonomy of requirements is created to classify the information gathered during the problem definition. Subsequently, the operational and systems functions and measures of effectiveness are integrated to a hierarchical model to allow the traceability of the information. Monte Carlo methods are used to evaluate the variations of the hierarchical model elements and consequently reduce the epistemic uncertainty. The proposed methodology is applied to the design of a hurricane tracker Unmanned Aerial Vehicles to demonstrate the origin and impact of requirements on the concept of operations and systems alternatives. This research demonstrates that the hierarchical modeling methodology provides a traceable flow-down of the requirements from the problem definition to the systems alternatives phases of conceptual design.

This research work provides the development of an Adaptive Flight Control System (AFCS) for autonomous hover of a Rotary-wing Unmanned Aerial Vehicle (RUAV). Due to the complex, nonlinear and time-varying dynamics of the RUAV, indirect adaptive control using the Model Predictive Control (MPC) is utilised. The performance of the MPC mainly depends on the model of the RUAV used for predicting the future behaviour. Due to the complexities associated with the RUAV dynamics, a neural network based black box identification technique is used for modelling the behaviour of the RUAV. Auto-regressive neural network architecture is developed for offline and online modelling purposes. A hybrid modelling technique that exploits the advantages of both the offline and the online models is proposed. In the hybrid modelling technique, the predictions from the offline trained model are corrected by using the error predictions from the online model at every sample time. To reduce the computational time for training the neural networks, a principal component analysis based algorithm that reduces the dimension of the input training data is also proposed. This approach is shown to reduce the computational time significantly. These identification techniques are validated in numerical simulations before flight testing in the Eagle and RMAX helicopter platforms. Using the successfully validated models of the RUAVs, Neural Network based Model Predictive Controller (NN-MPC) is developed taking into account the non-linearity of the RUAVs and constraints into consideration. The parameters of the MPC are chosen to satisfy the performance requirements imposed on the flight controller. The optimisation problem is solved numerically using nonlinear optimisation techniques. The performance of the controller is extensively validated using numerical simulation models before flight testing. The effects of actuator and sensor delays and noises along with the wind gusts are taken into account during these numerical simulations. In addition, the robustness of the controller is validated numerically for possible parameter variations. The numerical simulation results are compared with a base-line PID controller. Finally, the NN-MPCs are flight tested for height control and autonomous hover. For these, SISO as well as multiple SISO controllers are used. The flight tests are conducted in varying weather conditions to validate the utility of the control technique. The NN-MPC in conjunction with the proposed hybrid modelling technique is shown to handle additional disturbances successfully. Extensive flight test results provide justification for the use of the NN-MPC technique as a reliable technique for control of non-linear complex dynamic systems such as RUAVs.

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2011. / This thesis describes the design and implementation of a video compression development board as a standalone embedded system. The board can capture images, encode them and stream out a video to a destination over a wireless link. This project was done to allow users to test and develop video compression encoders that are designed for UAV applications. The board was designed to use an ADSP-BF533 Blackfin DSP from Analog Devices with the purpose of encoding images, which were captured by a camera module and then streamed out a video through a WiFi module. Moreover, an FPGA that has an interface to a logic analyzer, the DSP, the camera and the WiFi module, was added to accommodate other future uses, and to allow for the debugging of the board. The board was tested by loading a H.264 BP/MP encoder from Analog Devices to the DSP, where the DSP was integrated with the camera and the WiFi module. The test was successful and the board was able to encode a 2 MegaPixel picture at about 2 frames per second with a data rate of 186 Kbps. However, as the frame rate was only 2 frames per second, the video was somewhat jerky. It was found that the encoding time is a system limitation and that it has to be improved in order to increase the frame rate. A proposed solution involves dividing the captured picture into smaller segments and encoding each segment in parallel. Thereafter, the segments can be packed and streamed out. Further performance issues about the proposed structure are presented in the thesis.

Thesis (MEng)-- Stellenbosch University, 2013. / ENGLISH ABSTRACT: The deployment of Unmanned Aerial Vehicles (UAV) for power line inspection requires the definition of safe-fly zones. Transient Over-Voltages (TOVs) on the Overhead Transmission Lines (OHTLs) put the UAV at risk if it encroaches on these zones. In order to determine the safe-fly zones of a UAV in the vicinity of OHTLs, realistic full-scale experimental tests are done. Non-linearity in breakdown effects renders small-scale testing and computational work inaccurate. Experimental work is used to describe the close-up approach distances for worst-case scenarios. Testing cannot provide a full solution due to the limitation of the equipment available. Further tests must therefore be done at a specialised facility. Experiments are run in two phases, namely non-linear and linear tests in the High Voltage (HV) laboratory. The non-linear tests are done to derive Minimum Approach Distances (MAD). The linear experiments are used to calibrate FEKO, the simulation tool, to the measurement environment. Once correlation between the linear test data and the simulated data is found, confidence is derived in both the simulation model and the test setup. The simulations can then be used to determine a geometric factor as an input into F. Rizk’s prediction equations. The Rizk equations are used to describe the safe-fly zones alongside OHTLs as an addition to the non-linear experimental work. Along with the standard’s suggestions, the Rizk predictions are formulated in such a way that line-specific solutions can be determined. The suggested clearance values are provided in terms of per unit values, which can be selected in accordance with historical line data. Power line sparking is investigated to better understand the line radiation phenomenon. This understanding could assist in the line inspection process, as well as in the layout of power lines near radio quiet areas. Knowledge of OHTL radiation patterns can aid in the location of corona and sparking sources in the inspection process. Aerial sparking measurements are taken using a UAV carrying a spectrum analyser. Measured sparking levels are used to verify a Computational Electromagnetic (CEM) model. The CEM model can then be used to further investigate OHTL radiation characteristics. / AFRIKAANSE OPSOMMING: Die aanwending van Onbemande Vliegtuie (UAVs) vir kraglyn inspeksies, vereis die definiëring van veilige vlieg sones. Oorspannings (TOVs) op oorhoofse kraglyne (OHTLs) kan hierdie vliegtuie in gevaar stel as hulle die grense van hierdie sones oorskry. Om die veilige vlieg sones van 'n UAV in die omgewing van OHTLs te bepaal, is realistiese volskaalse toetse gedoen. Die nie-lineariteit in afbreek effekte lewer onakkurate kleinskaal toetse en rekenaar werk. Eksperimentele werk word gebruik om die benaderde afstande vir die ergste geval te beskryf. Hierdie werk kan nie 'n volledige oplossing gee nie as gevolg van ‘n beperking op huidige toerusting. Dit beteken dat verdere toetse, by ‘n meer gespesialiseerde fasiliteit, gedoen moet word. Eksperimente is uitgevoer in twee fases: nie-lineêre en lineêre toetse in die Hoogspannings (HV) laboratorium. Die nie-lineêre toetse word gedoen om die kleinste-benaderde-afstand (MAD) af te lei en die lineêre eksperimente word gebruik om FEKO (‘n numeriese elektromagnetika simulasie program) met die metings omgewing te kalibreer. Sodra daar ‘n korrelasie tussen die lineêre data en die gesimuleerde data is, kan daar aangeneem word dat die simulasie model en die toets-opstelling betroubaar is. Die simulasies kan dan gebruik word om 'n meetkundige faktor te bepaal as 'n bydrae tot F. Rizk se voorspellings vergelykings. Die Rizk vergelykings word gebruik om die veilige vlieg sones langs die OHTLs te beskryf. Dit kan dus gebruik word as ‘n toevoeging tot die nie-lineêre eksperimentele werk. Saam met die normale meet standaard voorstellings, is die Rizk voorspellings geformuleer sodat dit die lyn spesifieke oplossings kan bepaal. Die voorgestelde verklarings waardes word in per eenheid waardes beskryf, wat dan gekies kan word met ooreenstemmende historiese lyn data. Kraglyn-vonke word ondersoek om die lyn-bestraling verskynsel beter te verstaan. Hierdie begrip kan in die lyn inspeksie proses en in die uitleg van kraglyne naby radiostilte-areas help. Kennis van OHTL bestralings patrone kan help met die identifisering van corona en vonk-bronne tydens die inspeksie proses. 'n UAV met 'n aangehegte spektrum analiseerder is gebruik om die lug-vonkende metings te neem. Vonk vlakke wat gemeet is word dan gebruik om 'n Numeriese Elektromagnetiese (CEM) model te bevestig. Die CEM model kan dan gebruik word om OHTL bestralings eienskappe verder te ondersoek.

Made available in DSpace on 2016-08-31T13:33:46Z (GMT). No. of bitstreams: 1 MoniqueFS_Dissert.pdf: 2578055 bytes, checksum: 595fd4f8c3d8d5457fa6c6eb6df6adff (MD5) Previous issue date: 2015-08-27 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / The Unmanned Aerial Vehicles (UAVs) have received increasing attention in recent years as a way to replace the expensive manned vehicles. At first, UAVs were used for military applications, and currently they are used in the research and development area, where control techniques for stability and airworthiness are the main objects of study. The full development of autonomous flight in all environments is still a challenge. In this regard, the general objective of this work is to control the propulsion system of a quadrotor UAV for indoor altitude control application. The quadrotor system developed in this work consists of frame, four propellers, flight controller, sensors, four brushless direct current motors (BLDC), electronic speed controller (ESC), battery, radio control transmitter, receiver and universal circuit battery eliminator (UBEC). The software used for the simulation of Proportional Integral Derivative (PID) control for motor speed and altitude control was Simulink®/MATLAB. For the control development, it was necessary to model the quadrotor system to obtain a mathematical representation that allows an analytical study consistent with the system behavior in practice. The mathematical modeling of the quadrotor was performed using the Euler-Lagrange formalism, because it has the same form in any system of generalized coordinates and it is more suitable for generalizations. Tests were done to ensure proper operation of each part of the system, and quadrotor experiments were performed to calculate the motor thrust factor and to identificate parameters of BLDC motors. From the parameters identified in the experiments, the transfer functions required in PID control simulation of BLDC motor speed and quadrotor altitude were obtained. The experiment relating to PID control of motor speed was performed and the obtained values were compared with the simulated ones. The simulations and tests showed expected responses compared to the results of studies reported in the literature. This work begins new researches on UAVs area at the Universidade Federal Rural do Semi-Árido (UFERSA) / Os Veículos Aéreos Não Tripulados (VANTs) têm recebido uma crescente atenção nos últimos anos como uma forma de substituir os veículos tripulados de alto custo. Inicialmente, os VANTs eram usados para aplicações militares e, atualmente são utilizados na área de pesquisa e desenvolvimento, onde as técnicas de controle para a estabilidade e navegabilidade de voos são os principais objetos de estudo. O desenvolvimento completo de voo autônomo em todos os ambientes ainda é um desafio. Neste sentido, o objetivo geral do trabalho é controlar o sistema de propulsão de um VANT do tipo quadricóptero para aplicação no controle de altitude do mesmo em ambientes fechados. O sistema do quadricóptero desenvolvido neste trabalho é composto por frame, quatro hélices, controlador de voo, sensores, quatro motores de corrente contínua sem escovas (BLDC), controlador de velocidade eletrônico (ESC), bateria, transmissor rádio-controlado, receptor e circuito universal eliminador de bateria (UBEC). O software utilizado para simulação do controle Proporcional Integral Derivativo (PID) de velocidade dos motores e do controle de altitude foi o Simulink®/MATLAB. Para o desenvolvimento do controle foi necessário modelar o sistema do quadricóptero para obter uma representação matemática que permita um estudo analítico coerente com o comportamento do sistema na prática. A modelagem matemática do quadricóptero foi realizada através do formalismo de Euler-Lagrange, por possuir a mesma forma em qualquer sistema de coordenadas generalizadas e ser mais adequado a generalizações. Testes foram feitos a fim de garantir o funcionamento adequado de cada parte do sistema do quadricóptero e experimentos foram realizados para o cálculo do fator de empuxo dos motores e para a identificação de parâmetros dos motores BLDC. A partir dos parâmetros identificados nos experimentos, foram obtidas as funções de transferência necessárias para serem utilizadas nas simulações de controle PID de velocidade do motor BLDC e de altitude do quadricóptero. Foi realizado o experimento referente ao controle PID de velocidade do motor e os valores obtidos foram comparados com os da simulação. As simulações e testes apresentaram respostas esperadas, comparados com os resultados de trabalhos relacionados na literatura. Este trabalho dá início a novas pesquisas na área de VANTs na Universidade Federal Rural do Semi-Árido (UFERSA)

A utilização de Veículos Aéreos Não Tripulados (VANTs), também chamados UAV (Unmanned Aerial Vehicle) vem ganhando espaço nas mais diversas áreas, tais como inspeções em linhas de transmissão e em torres de fracionamento de refinarias, entre outros. Já na construção civil, estudos recentes estão sendo focados na utilização dos VANTs para inspeção de pontes, viadutos e estradas. O presente trabalho visa fornecer uma análise para o uso de VANT na área civil, na detecção de manifestações patológicas em revestimentos de argamassa, de forma a auxiliar na procura por fissuras em fachadas, sobretudo aqueles que a visualização esteja prejudicada, seja pela distância ou pela acessibilidade difícil ao local. Este trabalho analisa possíveis implementações de dois algoritmos de processamentos de imagens desenvolvidos a partir da ferramenta MATLAB para a indicação de presença de fissuras na alvenaria, obtendo o desempenho destes diferentes algoritmos quando executados em software em plataforma que possibilite a embarcação em VANTs. Utilizando a geração automática de código em C a partir do ambiente MATLAB, é realizada uma análise temporal em plataforma ARM e RISC dos algoritmos propostos, demonstrando a oportunidade de utilização de dispositivos na tarefa de processamento de imagem para a aplicação proposta. Esta análise possibilita a previsão do comportamento na utilização de um VANT, uma vez que isto pode impactar na velocidade durante a aplicação e consequentemente sua autonomia. / The use of Unmanned Aerial Vehicles (UAVs), has been gaining space in several areas, such as inspections of transmission lines, refineries fractionation towers among others. In the construction, recent studies have been focused on the use of UAVs for inspection of bridges, viaducts and roads. The present study aims to provide an analysis using UAVs in the civil construction area, in the detection of pathologic manifestations mortar coatings in order to aid in the search for cracks in the facades especially those that visualization is impaired, or may be the distance the accessibility difficult to spot. This paper provides an analysis of two algorithms of image processing developed from the Matlab tool for indicating the presence of cracks in masonry, getting the performance of these different algorithms when implemented in software platform that enables the vessel in UAV. Using the automatic generation of C/C++ code from the MATLAB environment is performed the temporal analysis on ARM and RISC plataform of the proposed algorithms demonstrates the opportunity to use devices in the image processing task for the proposed application. This analysis allows the prediction of the behavior of a UAV using one since it can impact velocity during application, and therefore their autonomy.

Detecção de linhas de alta tensão em ambientes complexos é uma das tarefas mais desafiadoras em inspeções que utilizam Veículos Aéreos Não Tripulados (VANTs). Este trabalho foca em dar uma solução para este desafio, através do desenvolvimento de um algoritmo de controle de voo de precisão, que guie o VANT de maneira autônoma sobre as linhas de alta tensão. O algoritmo proposto é baseado em quatro etapas: Captura da Imagem, Filtragem da Imagem, Detecção das Linhas e Controle de Voo. Inicialmente a imagem é redimensionada para um tamanho em que as linhas fiquem em maior evidência, depois uma sequência de filtros é aplicada na imagem para reduzir ruído e evidenciar ainda mais as linhas. Depois deste pré-tratamento, um filtro de duas dimensões com formato similar ao de uma linha de alta tensão é usado para extrair os pixels pertencentes as bordas destas linhas. Após a aplicação do filtro de duas dimensões, a Transformada de Hough é aplicada na imagem resultante para detectar os segmentos de reta. Por fim, todos os dados obtidos no processamento da imagem são utilizados para guiar o VANT de maneira autônoma pelas linhas de transmissão. O algoritmo proposto apresenta um eficiente sistema de detecção de linhas de alta tensão, para auxiliar o controle de voo autônomo de um VANT, apresentando resultados convincentes. / Power lines detection in complex environments is one of the most important and challenging tasks in Unmanned Aerial Vehicles (UAV)-based inspections. This work focuses on tackling this challenge by developing a control algorithm to support fine grain UAV control to autonomously guide the aerial platform over the power lines. The proposed algorithm is based on four stages: Image Capturing, Image Filtering, Line Detection and Flight Control. Firstly, the image is cropped to a size that fits all the power lines, then a sequence of filters is applied in the image to reduce noise and highlight these lines. After all the image's pretreatment, a 2D filter with similar shape of a power transmission line is used to extract pixels that belongs to the line's edges. Then, the Hough Transform method detects the line segments in the edges result image. Lastly all the obtained data is used to autonomously guide a UAV over the power transmission lines. The proposed algorithm presents an efficient power transmission lines detecting system to support the autonomous UAV guidance, which presents convincing results.

Detecção de linhas de alta tensão em ambientes complexos é uma das tarefas mais desafiadoras em inspeções que utilizam Veículos Aéreos Não Tripulados (VANTs). Este trabalho foca em dar uma solução para este desafio, através do desenvolvimento de um algoritmo de controle de voo de precisão, que guie o VANT de maneira autônoma sobre as linhas de alta tensão. O algoritmo proposto é baseado em quatro etapas: Captura da Imagem, Filtragem da Imagem, Detecção das Linhas e Controle de Voo. Inicialmente a imagem é redimensionada para um tamanho em que as linhas fiquem em maior evidência, depois uma sequência de filtros é aplicada na imagem para reduzir ruído e evidenciar ainda mais as linhas. Depois deste pré-tratamento, um filtro de duas dimensões com formato similar ao de uma linha de alta tensão é usado para extrair os pixels pertencentes as bordas destas linhas. Após a aplicação do filtro de duas dimensões, a Transformada de Hough é aplicada na imagem resultante para detectar os segmentos de reta. Por fim, todos os dados obtidos no processamento da imagem são utilizados para guiar o VANT de maneira autônoma pelas linhas de transmissão. O algoritmo proposto apresenta um eficiente sistema de detecção de linhas de alta tensão, para auxiliar o controle de voo autônomo de um VANT, apresentando resultados convincentes. / Power lines detection in complex environments is one of the most important and challenging tasks in Unmanned Aerial Vehicles (UAV)-based inspections. This work focuses on tackling this challenge by developing a control algorithm to support fine grain UAV control to autonomously guide the aerial platform over the power lines. The proposed algorithm is based on four stages: Image Capturing, Image Filtering, Line Detection and Flight Control. Firstly, the image is cropped to a size that fits all the power lines, then a sequence of filters is applied in the image to reduce noise and highlight these lines. After all the image's pretreatment, a 2D filter with similar shape of a power transmission line is used to extract pixels that belongs to the line's edges. Then, the Hough Transform method detects the line segments in the edges result image. Lastly all the obtained data is used to autonomously guide a UAV over the power transmission lines. The proposed algorithm presents an efficient power transmission lines detecting system to support the autonomous UAV guidance, which presents convincing results.

A utilização de Veículos Aéreos Não Tripulados (VANTs), também chamados UAV (Unmanned Aerial Vehicle) vem ganhando espaço nas mais diversas áreas, tais como inspeções em linhas de transmissão e em torres de fracionamento de refinarias, entre outros. Já na construção civil, estudos recentes estão sendo focados na utilização dos VANTs para inspeção de pontes, viadutos e estradas. O presente trabalho visa fornecer uma análise para o uso de VANT na área civil, na detecção de manifestações patológicas em revestimentos de argamassa, de forma a auxiliar na procura por fissuras em fachadas, sobretudo aqueles que a visualização esteja prejudicada, seja pela distância ou pela acessibilidade difícil ao local. Este trabalho analisa possíveis implementações de dois algoritmos de processamentos de imagens desenvolvidos a partir da ferramenta MATLAB para a indicação de presença de fissuras na alvenaria, obtendo o desempenho destes diferentes algoritmos quando executados em software em plataforma que possibilite a embarcação em VANTs. Utilizando a geração automática de código em C a partir do ambiente MATLAB, é realizada uma análise temporal em plataforma ARM e RISC dos algoritmos propostos, demonstrando a oportunidade de utilização de dispositivos na tarefa de processamento de imagem para a aplicação proposta. Esta análise possibilita a previsão do comportamento na utilização de um VANT, uma vez que isto pode impactar na velocidade durante a aplicação e consequentemente sua autonomia. / The use of Unmanned Aerial Vehicles (UAVs), has been gaining space in several areas, such as inspections of transmission lines, refineries fractionation towers among others. In the construction, recent studies have been focused on the use of UAVs for inspection of bridges, viaducts and roads. The present study aims to provide an analysis using UAVs in the civil construction area, in the detection of pathologic manifestations mortar coatings in order to aid in the search for cracks in the facades especially those that visualization is impaired, or may be the distance the accessibility difficult to spot. This paper provides an analysis of two algorithms of image processing developed from the Matlab tool for indicating the presence of cracks in masonry, getting the performance of these different algorithms when implemented in software platform that enables the vessel in UAV. Using the automatic generation of C/C++ code from the MATLAB environment is performed the temporal analysis on ARM and RISC plataform of the proposed algorithms demonstrates the opportunity to use devices in the image processing task for the proposed application. This analysis allows the prediction of the behavior of a UAV using one since it can impact velocity during application, and therefore their autonomy.

A utilização de Veículos Aéreos Não Tripulados (VANTs), também chamados UAV (Unmanned Aerial Vehicle) vem ganhando espaço nas mais diversas áreas, tais como inspeções em linhas de transmissão e em torres de fracionamento de refinarias, entre outros. Já na construção civil, estudos recentes estão sendo focados na utilização dos VANTs para inspeção de pontes, viadutos e estradas. O presente trabalho visa fornecer uma análise para o uso de VANT na área civil, na detecção de manifestações patológicas em revestimentos de argamassa, de forma a auxiliar na procura por fissuras em fachadas, sobretudo aqueles que a visualização esteja prejudicada, seja pela distância ou pela acessibilidade difícil ao local. Este trabalho analisa possíveis implementações de dois algoritmos de processamentos de imagens desenvolvidos a partir da ferramenta MATLAB para a indicação de presença de fissuras na alvenaria, obtendo o desempenho destes diferentes algoritmos quando executados em software em plataforma que possibilite a embarcação em VANTs. Utilizando a geração automática de código em C a partir do ambiente MATLAB, é realizada uma análise temporal em plataforma ARM e RISC dos algoritmos propostos, demonstrando a oportunidade de utilização de dispositivos na tarefa de processamento de imagem para a aplicação proposta. Esta análise possibilita a previsão do comportamento na utilização de um VANT, uma vez que isto pode impactar na velocidade durante a aplicação e consequentemente sua autonomia. / The use of Unmanned Aerial Vehicles (UAVs), has been gaining space in several areas, such as inspections of transmission lines, refineries fractionation towers among others. In the construction, recent studies have been focused on the use of UAVs for inspection of bridges, viaducts and roads. The present study aims to provide an analysis using UAVs in the civil construction area, in the detection of pathologic manifestations mortar coatings in order to aid in the search for cracks in the facades especially those that visualization is impaired, or may be the distance the accessibility difficult to spot. This paper provides an analysis of two algorithms of image processing developed from the Matlab tool for indicating the presence of cracks in masonry, getting the performance of these different algorithms when implemented in software platform that enables the vessel in UAV. Using the automatic generation of C/C++ code from the MATLAB environment is performed the temporal analysis on ARM and RISC plataform of the proposed algorithms demonstrates the opportunity to use devices in the image processing task for the proposed application. This analysis allows the prediction of the behavior of a UAV using one since it can impact velocity during application, and therefore their autonomy.