This study aimed to develop and evaluate a method to obtain a proportional-integral-derivative (PID) controller. The controller is for a control surface that controls pitch motion, by using data from flight tests with an unmanned aerial vehicle (UAV). Finding a suitable method to develop the controllers is essential to make the UAV autonomous, whilst being stable and controllable. Before developing the PID, data from test flights were used to model a transfer function for the control surface with MATLAB's toolbox for system identification. Thereafter, using the transfer function, the PID was developed by using MATLAB’s toolbox for control systems. The whole method was evaluated by studying the rise time, settling time, and overshoot for the PID, and studying how well the transfer function fits with the flight data. The method of modeling the pitch motion with system identification and finding the PID gains has good potential to simplify the process of finding a PID controller. However, to acquire an accurate model for the pitch motion, which in turn can give a well-performing PID, an improved data sampling was suggested. Additionally, flight tests conducted before and after PID tuning, and in different conditions are recommended to be done in future studies. The flight test would work as a validation for the model to acquire a robust PID that performs as expected. / Syftet med denna studie var att utveckla och utvärdera en metod för att hitta en proportionerlig integrerande deriverande (PID) regulator. Regulatorn är för en kontrollyta som kontrollerar tipprörelsen genom att använda data från flygtester med en drönare. Att hitta en lämplig metod för att utveckla regulatorer är nödvändigt för att göra drönaren autonom, samtidigt som den är stabil och kontrollerbar. Innan PID:n utvecklades användes data från flygtester för att modellera överföringsfunktionen för kontrollytan med MATLAB:s programvara för systemidentifiering. Därefter, genom att använda överföringsfunktionen, utvecklades PID:n med MATLAB:s programvara för reglersystem. Hela metoden utvärderades genom att studera stigtid, insvängningstid och översläng för PID regulatorn, samt studera hur väl överföringsfunktionen modellerar flygdata. Metoden för att modellera tipprörelsen och att hitta PID förstärkningarna har en god potential att förenkla processen av att hitta en PID regulator. Däremot för att få en precis modell för tipprörelsen, vilket i sin tur kan ge en välpresterande PID, föreslogs det att förbättra datainsamlingen. Dessutom rekommenderades det i framtida studier att flygtester genomförs i olika förhållande, både före och efter att PID regulatorn har hittats. Flygtesterna skulle fungera som en bekräftelse för modellen för att få en robust PID som presterar som väntat. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

Thesis (MScEng)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: The landing phase of any helicopter is the most critical part of the whole flight envelope, particularly on a moving flight deck. The flight deck is usually located at the stern of the ship, translating to large heave motions. This thesis focuses on the three fundamental components required for a successful landing: accurate, relative state-estimation between the helicopter and the flight deck; a prediction horizon to forecast suitable landing opportunities; and excellent control to safely unite the helicopter with the flight deck. A monocular-vision sensor node was developed to provide accurate, relative position and attitude information of the flight deck. The flight deck is identified by a distinct, geometric pattern. The relative states are combined with the onboard, kinematic state-estimates of the helicopter to provide an inertial estimate of the flight deck states. Onboard motion prediction is executed to forecast a possible safe landing time which is conveyed to the landing controller. Camera pose-estimation tests and hardware-in-the-loop simulations proved the system developed in this thesis viable for flight tests. The practical flight tests confirmed the success of the monocular-vision sensor node. / AFRIKAANSE OPSOMMING: Die mees kritiese deel van die hele vlug-duurte van ’n helikopter is die landings-fase, veral op ’n bewegende vlugdek. Die vlugdek is gewoonlik geleë aan die agterstewe-kant van die skip wat groot afgee bewegings mee bring. Hierdie tesis ondersoek die drie fundamentele komponente van ’n suksesvolle landing: akkurate, relatiewe toestand-beraming tussen die helikopter en die vlugdek; ’n vooruitskatting horison om geskikte landings geleenthede te voorspel; en uitstekended beheer om die helikopter en vlugdek veilig te verenig. ’n Monokulêre-visie sensor-nodus was ontwikkel om akkurate, relatiewe-posisie en oriëntasie informasie van die vlugdek te verwerf. Die vlugdek is geidentifiseer deur ’n kenmerkende, geometriese patroon. Die relatiewe toestande word met die aan-boord kinematiese toestandafskatter van die helikopter gekombineer, om ’n beraming van die inertiale vlugdek-toestande te verskaf. Aan-boord beweging-vooruitskatting is uitgevoer om moontlike, veilige landingstyd te voorspel en word teruggevoer na die landingsbeheerder. Kamera-orientasie afskat-toetse en hardeware-in-die-lus simulasies het die ontwikkelde sisteem van hierdie tesis lewensvatbaar vir vlug-toetse bewys. Praktiese vlug-toetse het die sukses van die monokulêre-visie sensor-nodus bevestig.

Unmanned Aerial Vehicles (UAVs) provides a platform for many automated tasks and with an ever increasing advances in computing, these tasks can be more complex. The use of UAVs is expanded in this thesis with the goal of Search and Rescue (SAR), where a UAV can assist fast responders to search for a lost person and relay possible search areas back to SAR teams. To identify a person from an aerial perspective, low-level Histogram of Oriented Gradients (HOG) feature descriptors are used over a segmented region, provided from thermal data, to increase classification speed. This thesis also introduces a dataset to support a Bird’s-Eye-View (BEV) perspective and tests the viability of low level HOG feature descriptors on this dataset. The low-level feature descriptors are known as Boosted Histogram of Oriented Gradients (BHOG) features, which discretizes gradients over varying sized cells and blocks that are trained with a Cascaded Gentle AdaBoost Classifier using our compiled BEV dataset. The classification is supported by multiple sensing modes with color and thermal videos to increase classification speed. The thermal video is segmented to indicate any Region of Interest (ROI) that are mapped to the color video where classification occurs. The ROI decreases classification time needed for the aerial platform by eliminating a per-frame sliding window. Testing reveals that with the use of only color data iv and a classifier trained for a profile of a person, there is an average recall of 78%, while the thermal detection results with an average recall of 76%. However, there is a speed up of 2 with a video of 240x320 resolution. The BEV testing reveals that higher resolutions are favored with a recall rate of 71% using BHOG features, and 92% using Haar-Features. In the lower resolution BEV testing, the recall rates are 42% and 55%, for BHOG and Haar-Features, respectively.

Approved for public release; distribution is unlimited / An increasing number of unmanned vehicles (UV) are being incorporated into maritime operations as organic elements of Expeditionary and Carrier Strike Groups for development of the recognized maritime picture. This thesis develops an analytically-based planning aid for allocating UVs to missions. Inputs include the inventory of UVs, sensors, their performance parameters, and operational scenarios. Operations are broken into mission critical functions: detection, identification, and collection. The model output assigns aggregated packages of UVs and sensors to one of the three functions within named areas of interest. A spreadsheet model uses conservative time-speed-distance calculations, and simplified mathematical models from search theory and queuing theory, to calculate measures of performance for possible assignments of UVs to missions. The spreadsheet model generates a matrix as input to a linear integer program assignment model which finds the best assignment of UVs to missions based on the user inputs and simplified models. The results provide the mission planner with quantitatively-based recommendations for unmanned vehicle mission tasking in challenging scenarios. / Lieutenant, United States Navy

De nos jours, les applications utilisant des quadrirotors autonomes sont en plein essor. La surveillance et la sécurité de sites industriels ou sensibles, de zones géographiques pour l’agriculture par exemple sont quelques-unes des applications les plus célèbres des véhicules aériens sans pilote (UAV). Actuellement, certains chercheurs et scientifiques se concentrent sur le déploiement multi-drones pour l’inspection et la surveillance de vastes zones. L’objectif de cette thèse est de concevoir des algorithmes afin de réaliser une commande de vol en formation distribuée/décentralisée de multi-UAVs en temps réel dans une perspective de systèmes de systèmes. Tout d’abord, nous avons passé en revue certains travaux récents de la littérature sur la commande de vol en formation et la commande de quadrirotors. Nous avons présenté une brève introduction sur les systèmes de systèmes, leur définition et leurs caractéristiques. Ensuite, nous avons introduit la commande de vol en formation avec ses structures les plus utilisées dans la littérature. Nous avons alors présenté quelques travaux existants traitant du flocking (comportement de regroupement en flotte), les méthodes de modélisation les plus utilisés pour les quadrirotors et quelques approches de commande les plus utilisées pour stabiliser des quadrirotors. Deuxièmement, nous avons utilisé la structure de la commande comportementale pour réaliser un vol en formation de plusieurs UAVs. Nous avons conçu un comportement pour réaliser le vol en formation de multi-UAVs sans fragmentation. Le comportement proposé traite le problème flocking dans une perspective globale, c’est-à-dire, nous avons inclus une tendance dans chaque drone pour former une formation. Les défis des Systèmes de systèmes nous a motivés à chercher des algorithmes de flocking et de consensus introduits dans la littérature qui peuvent être utiles pour répondre à ces défis. Cela nous a amenés à proposer quatre lois de commande en visant à être compatibles avec le modèle non linéaire des quadrirotors et pouvant être expérimentés sur des plates-formes réelles. Les lois de commande ont été exécutées à bord de chaque quadrirotor dans la formation et chaque quadrirotor interagit avec ses voisins pour assurer un vol en formation sans collision. Enfin, nous avons validé nos lois de commande par des simulations et des expériences en temps réel. Pour la simulation, nous avons utilisé un simulateur de multi quadrirotors développé au laboratoire Heudiasyc. Pour les expériences, nous avons mis en œuvre nos lois de contrôle sur des quadrirotors ArDrone2 évolués dans un environnement intérieur équipé d’un système de capture de mouvement (Optitrack). / Nowadays, applications of autonomous quadrotors are increasing rapidly. Surveillance and security of industrial sites, geographical zones for agriculture for example are some popular applications of Unmanned Aerial Vehicles (UAVs). Nowadays, researchers and scientists focus on the deployment of multi-UAVs for the inspection and the surveillance of large areas. The objective of this thesis is to design algorithms and techniques to perform a real-time distributed/decentralized multi-UAVs flight formation control, from a system of systems perspective. Firstly, we reviewed recent works of the literature about flight formation control and the control of quadrotors. We presented a brief introduction about systems of systems, their definition and characteristics. Then, we introduced the flight formation control with its most used structures in the literature, some existing works dealing with flocking. Finally, we presented the most used modeling methodologies for quadrotors and some control approaches that are used to stabilize quadrotors. Secondly, we used the behavioral-based control structure to achieve a multiple UAV flocking. We conceived a behavior intending to address the control design towards a successful achievement of the flocking task without fragmentation. The proposed behavior treats the flocking problem from a global perspective, that is, we included a tendency of separated UAVs to form a flock.System of systems challenges motivated us to look for flocking and consensus algorithms introduced in the literature that could be helpful to answer to these challenges. This led us to propose four flocking control laws aiming at being compatible with the nonlinear model of quadrotors and at being implemented on experimental platforms. The control laws were run aboard each quadrotor in the flock. By running the control law, each quadrotor interacts with its neighbors to ensure a collision-free flocking. Finally, we validated our proposed control laws by simulations and real-time experiments. For the simulation, we used a PC-based simulator of flock of multiple quadrotors which was developed at Heudiasyc laboratory. For experiments, we implemented our control laws on ArDrone2 quadrotors evolved in an indoor environment equipped with an Optitrack motion capture system.