Flight testing methods are developed to find the drag polar for small UAVs powered by electric motors with fixed-pitch propellers. Wind tunnel testing was used to characterize the propeller-motor efficiency. The drag polar was constructed using data from flight tests. The proposed methods were implemented for a small UAV. A drag polar was found for this aircraft with CDo equal to 0.021, K1 equal to 0.229, and K2 equal to -0.056. This drag polar was then used to find the following performance parameters; maximum velocity, minimum velocity, velocity for maximum range, velocity for maximum endurance, maximum rate of climb, maximum climb angle, minimum turn radius, maximum turn rate, and maximum bank angle. Applications in UAV control and mission planning are also proposed.

An adaptive autopilot design for an uninhabited surface vehicle Andy SK Annamalai The work described herein concerns the development of an innovative approach to the design of autopilot for uninhabited surface vehicles. In order to fulfil the requirements of autonomous missions, uninhabited surface vehicles must be able to operate with a minimum of external intervention. Existing strategies are limited by their dependence on a fixed model of the vessel. Thus, any change in plant dynamics has a non-trivial, deleterious effect on performance. This thesis presents an approach based on an adaptive model predictive control that is capable of retaining full functionality even in the face of sudden changes in dynamics. In the first part of this work recent developments in the field of uninhabited surface vehicles and trends in marine control are discussed. Historical developments and different strategies for model predictive control as applicable to surface vehicles are also explored. This thesis also presents innovative work done to improve the hardware on existing Springer uninhabited surface vehicle to serve as an effective test and research platform. Advanced controllers such as a model predictive controller are reliant on the accuracy of the model to accomplish the missions successfully. Hence, different techniques to obtain the model of Springer are investigated. Data obtained from experiments at Roadford Reservoir, United Kingdom are utilised to derive a generalised model of Springer by employing an innovative hybrid modelling technique that incorporates the different forward speeds and variable payload on-board the vehicle. Waypoint line of sight guidance provides the reference trajectory essential to complete missions successfully. The performances of traditional autopilots such as proportional integral and derivative controllers when applied to Springer are analysed. Autopilots based on modern controllers such as linear quadratic Gaussian and its innovative variants are integrated with the navigation and guidance systems on-board Springer. The modified linear quadratic Gaussian is obtained by combining various state estimators based on the Interval Kalman filter and the weighted Interval Kalman filter. Change in system dynamics is a challenge faced by uninhabited surface vehicles that result in erroneous autopilot behaviour. To overcome this challenge different adaptive algorithms are analysed and an innovative, adaptive autopilot based on model predictive control is designed. The acronym ‘aMPC’ is coined to refer to adaptive model predictive control that is obtained by combining the advances made to weighted least squares during this research and is used in conjunction with model predictive control. Successful experimentation is undertaken to validate the performance and autonomous mission capabilities of the adaptive autopilot despite change in system dynamics.

In the last decade, the development and deployment of Uninhabited Airborne Vehicles (UAVs) has increased dramatically. This has in turn increased the desire to operate UAVs in civilian-airspace. Current UAV platforms can be integrated into civilian-airspace, with other air traffic, however they place a high burden on their human operators in order to do so. In order to meet the competing objectives of improved integration and low operator workload it will be necessary to increase the intelligence on-board the UAV. This thesis presents the results of the research which has been conducted into increasing the on-board intelligence of the UAV. The intent in increasing the on-board intelligence is to improve the ability of a UAV to integrate into civilian-airspace whilst also reducing the workload placed upon the UAV's operator. The research has focused upon increasing the intelligence in two key areas: mission planning; and mission piloting. Mission planning is the process of determining how to fly from one location to another, whilst avoiding entities (eg. airspace boundaries and terrain) on the way. Currently this task is typically performed by a trained human operator. This thesis presents a novel multidisciplinary approach for enabling a UAV to perform, on-board, its own mission planning. The novel approach draws upon techniques from the 3D graphics and robotics fields in order to enable the UAV to perform its own mission planning. This enables the UAV's operator to provide the UAV with the locations (waypoints) to fly to. The UAV will then determine for itself how to reach the locations safely. This relieves the UAV's operator of the burden of performing the mission planning for the UAV. As part of this novel approach to on-board mission planning, the UAV constructs and maintains an on-board situational awareness of the airspace environment. Through techniques drawn from the 3D graphics field the UAV becomes capable of constructing and interacting with a 3D digital representation of the civilian-airspace environment. This situational awareness is a fundamental component of enabling the UAV to perform its own mission planning and piloting. The mission piloting research has focused upon the areas of collision avoidance and communications. These are tasks which are often handled by a human operator. The research identified how these processes can be performed on-board the UAV through increasing the on-board intelligence. A unique approach to collision avoidance was developed, which was inspired by robotics techniques. This unique approach enables the UAV to avoid collisions in a manner which adheres to the applicable Civil Aviation Regulations, as defined by the Civil Aviation Safety Authority (CASA) of Australia. Furthermore, the collision avoidance algorithms prioritise avoiding collisions which would result in a loss of life or injury. Finally, the communications research developed a natural language-based interface to the UAV. Through this interface, the UAV can be issued commands and can also be provided with updated situational awareness information. The research focused upon addressing issues related to using natural language for a civilian-airspace-integrated UAV. This area has not previously been addressed. The research led to the definition of a vocabulary targeted towards a civilian-airspace-integrated UAV. This vocabulary caters for the needs of both Air Traffic Controllers and general UAV operators. This requires that the vocabulary cater for a diverse range of skill levels. The research established that a natural language-based communications system could be applied to a civilian-airspace-integrated UAV for both command and information updates. The end result of this research has been the development of the Intelligent Mission Planner and Pilot (IMPP). The IMPP represents the practical embodiment of the novel algorithms developed throughout the research. The IMPP was used to evaluate the performance of the algorithms which were developed. This testing process involved the execution of over 3000 hours of simulated flights. The testing demonstrated the high performance of the algorithms developed in this research. The research has led to the successful development of novel on-board situational awareness, mission planning, collision avoidance and communications capabilities. This thesis presents the development, implementation and testing of these capabilities. The algorithms which provide these capabilities go beyond the existing body of knowledge and provide a novel contribution to the established research. These capabilities enable the UAV to perform its own mission planning, avoid collisions and receive natural language-based communications. This provides the UAV with a direct increase in the intelligence on-board the UAV, which is the core objective of this research. This increased on-board intelligence improves the integration of the UAV into civilian-airspace whilst also reducing the operator's workload.

Uninhabited Aircraft Systems (UAS), as a relatively novel technology, was always seen as a tool available and utilized only by rich and developed states. But thanks to globalizations and the fast proliferation of commercially available drones, this platform has already been used by smaller states and also non-state groups, giving them possibilities never seen before. Yet, there is little research on how and why these new actors use UAS to claim their cause. The research question to guide this thesis is how and why do non-state armed groups differ from states when using Uninhabited Aircraft Systems in their military operations? The thesis uses a demand- and supply-side theory, adapted for the proliferation of drones to help answer that question. This theory is tested in a multiple case study involving the United States as a state and the Houthis as a non-state group during the Yemeni crisis, from 2011 to 2022. Through a structured, focused comparison between the cases, indicators from the demand- and supply-side models were used to understand the differences in drone use between different actors. The main findings are that states and non-state armed groups differ in their use of UAS mainly because they have different boundaries (legal and technological), but also for the symbol and status that this platform carries. Finally, it was seen that the theory is not only able to clarify the trends on proliferation, but also the why actors use UAS, with few remarks, but with a need to test it further.

博士(法学) / Doctor of Laws / 同志社大学 / Doshisha University

The world population is increasing and so is the housing shortage. 62 percent of Sweden's municipalities report a housing shortage. At the same time about 280 000 buildings in Sweden are abandoned. The purpose of this study is to investigate how municipalities can work to create better conditions to repopulate the abandoned houses in rural areas. This study is based on Uppvidinge municipality, but could also be applied in other municipalities in Sweden. To achieve a good result, both a semi-structured interview study, a literature review and a field study were conducted. The methods were chosen to provide a deeper understanding of the work other municipalities already have done regarding deserted houses. The research resulted in a strategy plan that describes how municipalities can work to identify abandoned houses and make them habitable again. The results showed that the inventory of abandoned houses should focus on communication rather than technical inventory work. In order for municipalities to succeed in the work of repopulating abandoned houses, they need financial support from politics, good communication and cooperation with other actors in the society, but also a passion for rural development.