<p>The use of lower airspace for air taxi and cargo applications opens up exciting prospects for futuristic Unmanned Aircraft Systems (UAS). However, ensuring the safety and security of these UAS within densely populated urban areas presents significant challenges. Most modern aircraft systems, whether unmanned or otherwise, rely on the Global Navigation Satellite System (GNSS) as a primary sensor for navigation. From satellite navigations point of view, the dense urban environment compromises positioning accuracy due to signal interference, multipath effects, etc. Furthermore, civilian GNSS receivers are susceptible to spoofing attacks since they lack encryption capabilities. Therefore, in this thesis, we focus on examining the safety and cybersecurity assurance of UAS in dense urban environments, from both theoretical and experimental perspectives. </p> <p>To facilitate the verification and validation of the UAS, the first part of the thesis focuses on the development of a realistic GNSS sensor emulation using a Gazebo plugin. This plugin is designed to replicate the complex behavior of the GNSS sensor in urban settings, such as multipath reflections, signal blockages, etc. By leveraging the 3D models of the urban environments and the ray-tracing algorithm, the plugin predicts the spatial and temporal patterns of GNSS signals in densely populated urban environments. The efficacy of the plugin is demonstrated for various scenarios including routing, path planning, and UAS cybersecurity. </p> <p>Subsequently, a robust state estimation algorithm for dynamical systems whose states can be represented by Lie Groups (e.g., rigid body motion) is presented. Lie groups provide powerful tools to analyze the complex behavior of non-linear dynamical systems by leveraging their geometrical properties. The algorithm is designed for time-varying uncertainties in both the state dynamics and the measurements using the log-linear property of the Lie groups. When unknown disturbances are present (such as GNSS spoofing, and multipath effects), the log-linearization of the non-linear estimation error dynamics results in a non-linear evolution of the linear error dynamics. The sufficient conditions under which this non-linear evolution of estimation error is bounded are derived, and Lyapunov stability theory is employed to design a robust filter in the presence of an unknown-but-bounded disturbance. </p>

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<p dir="ltr">In the context of a Human-in-the-Loop (HITL) system, the accuracy of reachability analysis plays a significant role in ensuring the safety and reliability of HITL systems. In addition, one can avoid unnecessary conservativeness by explicitly considering human control behavior compared to those methods that rely on the system dynamics alone. One possible approach is to use a Gaussian Mixture Model (GMM) to encode human control behavior using the Expectation-Maximization (EM) algorithm. However, relatively few works consider the admissible control input ranges due to physical limitations when modeling human control behavior. This could make the following reachability analysis overestimate the system's capability, thereby affecting the performance of the HITL system. To address this issue, this work presents a constrained stochastic reachability analysis algorithm that can explicitly account for the admissible control input ranges. By confining the ellipsoidal confidence region of each Gaussian component using Sequential Quadratic Programming (SQP), we probabilistically constrain the GMM as well as the corresponding stochastic reachable sets. A comprehensive mathematical analysis of how the constrained GMM can affect the stochastic reachable sets is provided in this work. Finally, the proposed stochastic reachability analysis algorithm is validated via an illustrative numerical example.</p>

<p dir="ltr">The use of autonomous vehicles, such as Unmanned Aerial Systems (UASs), Unmanned Ground Vehicles (UGVs), and Unmanned Surface Vessels (USVs), has globally increased in various applications. Their rising popularity and high accessibility have also increased the use of UASs in criminal or hazardous actions.</p><p dir="ltr">It is beneficial to rapidly compute possible surveillance system evasive paths to evaluate the effectiveness of a given sensor deployment scheme. To find these evasive trajectories, we assume full knowledge of the current and future state of the surveillance system. This assumption allows the defender to identify worst-case trajectories to counteract. The surveillance system path planning presented in this work can be leveraged for game theoretic sensor deployment.</p><p dir="ltr">A sensor deployment scheme determines the overall surveillance efficiency. Through redeployment after each assessment, it aims to approach an equilibrium that maximizes defense capabilities. Therefore, a method of evaluation that models mobile, directional sensors is demanded.</p><p dir="ltr">In response to this demand, this thesis explores the design of a computationally efficient path-planning algorithm for the space-time domain. The Space-Time Parallel RRT* (STP-RRT*) algorithm obtains multiple goal candidates, drawn from a uniform distribution over the time horizon. A set of parallel RRT* trees is simultaneously populated by each goal candidate. By leveraging a connect heuristic from RRT-Connect, parallel goal trees converge to an RRT* tree populated from a start point. This simultaneous tree growth structure returns a computation complexity of O(N log(N)), where N is the number of random samples.</p><p dir="ltr">Due to its low complexity, the STP-RRT* algorithm is suitable to be used as an evaluation metric that computes the cost of the infiltration path of a malicious autonomous system to assess the performance of the deployment layout. The feedback assessment can be used for the surveillance system redeployment to strengthen the vulnerability.</p><p dir="ltr">To identify potential and existing bottlenecks in the algorithm, a computation complexity analysis is conducted, and complexity reduction techniques are employed. Given that surveillance system characteristics are known, 1-dimensional and 2-dimensional environments are generated where positions and surveillance patterns of stationary and dynamic obstacles are randomly selected. In each randomized environment, the STP-RRT*, RRT*, and ST-RRT* are evaluated by comparing success rate, computation time, tree size, and normalized cost through 100-trial Monte Carlo simulations. Under the provided conditions, the proposed STP-RRT* algorithm outperforms two other algorithms with an improved mean success rate and reduced mean computation time by 10.02% and 12.88%, respectively, while maintaining a similar cost level, showing its potential application in surveillance-evasive path-planning problems for surveillance deployment evaluation. Finally, we integrate our algorithm with Nav2, an open-source navigation stack for various robotics applications, including UAV, UGV, and USV. We demonstrate its effectiveness via software-in-the-loop (SiTL) experiments utilizing open-source autopilot software.</p>

<p dir="ltr">I conducted an in-depth analysis of the frequency and severity of external load accidents involving Chinook helicopters over a period of 30 years. The literature review encompassed General Aviation (GA) and ground-based safety organizations, while the data analysis predominantly relied on secondary data from the Army Combat Readiness Center (ACRC). In conducting this study, I aimed to identify key trends, causes, and effects of these accidents, particularly emphasizing material failures, human errors, and the substantial impact of rotor downwash as horizontal wind velocities in proximity to the ground. The study's goal was to improve safety and operational efficiency in Chinook external load operations by identifying frequency and severity of accidents over a 30-year period. The hope was that this would provide valuable insights for improvements in risk mitigation techniques.</p><p dir="ltr">By using an exploratory secondary data analysis of both publicly available U.S. Army accidents and accident data provided by the U.S. ACRC, I found that Chinook rotor downwash, which manifests as horizontal wind velocity when in close proximity to the ground, is the most significant and underreported factor. Based on the findings of this research, I recommend improved classification and documentation of such accidents. The findings highlighted the urgency of updating training and operational procedures to effectively address the unique challenges posed by rotor downwash and high gross weights in proximity to the ground, typical of Chinook external load Pickup and Landing Zone (PZ/LZ) operations. Implementing these recommendations is expected to enhance safety measures in both training and practical operations, ultimately reducing future accidents and improving safety standards in the aviation industry.</p>

<p>In Chapter 2 an experiment has been conducted to measure the quenching distance of a premixed fuel-air mixture. Quenching distance refers to the physical limit below which combustion of a fuel and an oxidizer, even if present in sufficient proportions, cannot maintain combustion and propagate a flame. It is dependent on the physical area that is present for the flame to travel through, the temperature and pressure conditions, the thermal conductivity of the walls, and the specific fuel and oxidizer present. Applicable in a wide variety of industries from the automotive industry to the aerospace industry, the ability to control a combustion reaction and where it occurs can lead to increased safety and efficiency in devices such as injectors, mixing chambers, engine pistons, combustors, propellant turbopumps, and fuel-air heat exchangers. Currently, little to no quenching distance data exists for heavier-than-air hydrocarbons. Using a parallel ceramic plate setup with spark rods inside a pressure vessel to contain the initial combustion reaction, the quenching distances of the hydrocarbons is measured and a relationship with equivalence ratio is found. This relationship is used to construct a model to apply to heavier-than-air hydrocarbons.</p> <p>Chapter 3 focuses on an experiment designed to measure the flow rates of leaks in fuel-air heat exchangers. The ability to accurately quantify and understand these flow rates is crucial for assessing the performance and safety of such systems. Furthermore, the obtained flow rate data will be compared with a Computational Fluid Dynamics (CFD) model developed for micro-scale flows resulting from fuel leakage into a cross-flow of heated air within the heat exchanger. These flow rates provide a model of the volume and rate of fuel being injected into the air channels, aiding in the assessment of potential risks and hazards associated with the leakage. To validate the accuracy and reliability of the model developed for micro-scale flow, the measured flow rates obtained from the experimental setup are compared against the corresponding predictions of the model. By establishing a correlation between the experimental data and the model results, the validity of the model can be confirmed, ensuring its efficacy for future simulations and analyses.</p> <p>Chapter 4 details the creation and analysis of a program developed in Python and MATLAB for assessing combustion risk in microscale fuel-air heat exchanger channels. The Safety Net for Unquenched Flame Fronts (SNUFF) is designed as a design assistance tool for microscale flows of fuel and oxidizer, specifically for heat exchangers. This application helps analyze combustion risks in these microscale flow channels due to leaks or unintended flows caused by damage or manufacturing defects. SNUFF integrates REFPROP and flame simulation data with the models for quenching distance and microscale flow from previous chapters to generate sensitivity plots for various design parameters. This tool enables engineers to assess combustion risks in fuel-air channels, allowing them to design processes that accommodate manufacturing limitations in numerous microscale channel applications.</p>

<p dir="ltr">Managing transient heat loads has become more challenging with the increasing electrification of ground, air, and marine vehicles. Doing so requires novel designs of thermal management systems, or in some cases, novel retrofits of legacy TMSs to accommodate the addition of more electrified subsystems. However, design tools that are well suited for examining and optimizing the dynamic response of TMS over candidate operation or mission profiles are limited. In this thesis, a principled methodology and associated tools for the enumeration and dynamic optimization of all feasible architectures of an air cycle machine are presented. Graph-based modeling is pivotal for exploring and optimizing ACM architectures, providing a structured representation of system components and interactions. By modeling the ACM as a graph, with vertices and edges representing components and interactions, respectively, various component configurations and performance metrics can be systematically analyzed. This approach enables efficient exploration of design alternatives and consideration of dynamic boundary conditions (representing, for example, a complex mission profile) during optimization. Another unique contribution of this thesis is a novel application of a multi-state graph-based modeling approach for developing dynamic models of turbomachinery components. By representing multiple states within each control volume or component and connecting them through power flows, this approach accurately captures both first and second law dynamics, enabling the computation of dynamic entropy generation rates. A detailed case study demonstrates the optimization of ACM architectures based on entropy generation minimization and dynamic bleed air flow rate minimization. This study highlights the trade-offs between different optimization criteria and the potential for generalizing the tool to more complex thermofluid systems in thermal management applications. The results underscore the importance of entropy-based analysis in comparing the thermodynamic losses across various system architectures.</p>

International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and Conference Center, San Diego, California / The Aircraft Research and Development Unit (ARDU) of the Royal Australian Air Force (RAAF) is the only agency in Australia that performs the full spectrum of military flight testing and is the new custodian of the instrumented weapons range at Woomera. Receiving early attention will be the upgrade and integration of ARDU's telemetry systems with the meteorological and tracking data acquisition capabilities at Woomera to minimize overhead and data turnaround time. To achieve these goals, maximum modularity, extensibility, and product interoperability is being sought in the proposed architecture of all the systems that will need to cooperate on the forecast test programmes. These goals are also driven by the need to be responsive to a wide variety of tasks which presently include structural flight testing of fighter and training aircraft, weapons systems performance evaluation on a variety of combatant aircraft, and a host of other tasks associated with all fixed and rotary wing aircraft in the Army and Air Force inventory. Of all these tasks however, ARDU sees that responsiveness to future testing of F-111Cs fitted with unique Digital Flight Control Systems along with USAF standard F-111Gs may place the most significant demands on data handling —particularly in regard to providing an avionics bus diagnostic capability when performing Operational Flight Programme (OFP) changes to the mission computers. With the timely assistance and advice of Loral Test & Information Systems, who has long-term experience in supporting USAF F-111 test programmes, ARDU is confident of making wise design decisions that will provide the desired flexibility and, at the same time, minimize life-cycle costs by ensuring compliance with the appropriate telemetry and open systems standards. As well, via cooperative agreements with the USAF, the potential exists to acquire proven software products without needing to fund the development costs already absorbed by the USAF. This paper presents ARDU's perception of future needs, a view by LTIS of how best to meet those needs, and, based on ARDU data, a view of how LTIS' proposal will satisfy the requirement to provide maximum extensibility with minimum life-cycle costs.

Quad-rotor helicopters are agile aircraft which are lifted and propelled by four rotors. Unlike traditional helicopters, they do not require a tail-rotor to control yaw, but can use four smaller fixed-pitch rotors. However, without an intelligent control system it is very difficult for a human to successfully fly and manoeuvre such a vehicle. Thus, most of recent research has focused on small unmanned aerial vehicles, such that advanced embedded control systems could be developed to control these aircrafts. Vehicles of this nature are very useful when it comes to situations that require unmanned operations, for instance performing tasks in dangerous and/or inaccessible environments that could put human lives at risk. This research demonstrates a consistent way of developing a robust adaptive controller for quad-rotor helicopters, using fuzzy-neural networks; creating an intelligent system that is able to monitor and control the non-linear multi-variable flying states of the quad-rotor, enabling it to adapt to the changing environmental situations and learn from past missions. Firstly, an analytical dynamic model of the quad-rotor helicopter was developed and simulated using Matlab/Simulink software, where the behaviour of the quad-rotor helicopter was assessed due to voltage excitation. Secondly, a 3-D model with the same parameter values as that of the analytical dynamic model was developed using Solidworks software. Computational Fluid Dynamics (CFD) was then used to simulate and analyse the effects of the external disturbance on the control and performance of the quad-rotor helicopter. Verification and validation of the two models were carried out by comparing the simulation results with real flight experiment results. The need for more reliable and accurate simulation data led to the development of a neural network error compensation system, which was embedded in the simulation system to correct the minor discrepancies found between the simulation and experiment results. Data obtained from the simulations were then used to train a fuzzy-neural system, made up of a hierarchy of controllers to control the attitude and position of the quad-rotor helicopter. The success of the project was measured against the quad-rotor’s ability to adapt to wind speeds of different magnitudes and directions by re-arranging the speeds of the rotors to compensate for any disturbance. From the simulation results, the fuzzy-neural controller is sufficient to achieve attitude and position control of the quad-rotor helicopter in different weather conditions, paving way for future real time applications.

Au cours du siècle dernier, la communauté scientifique a traité le contrôle des véhicules aériens principalement par l'élaboration de stratégies ad hoc, mais aucune approche unifiée n'a été développé jusqu'à présent. Cette thèse participe à l'élaboration d'une approche unifiée pour le contrôle des véhicules aériens en prenant en compte les forces aérodynamiques dans la conception de la commande. Nous supposons les effets aérodynamiques de rotation et les effets non stationnaires négligeables. Les actionneurs du véhicule sont supposés être composés d'une force de poussé fixée au corps pour le mouvement en translation, et d'un couple de contrôle pour la régulation d'attitude. Cette thèse se concentre ensuite sur la boucle de guidage, traitant du contrôle de la vitesse linéaire. L'un des principaux objectifs a été de déterminer la façon de réguler la force de poussée et l'orientation du véhicule pour compenser les forces extérieures. Tout d'abord nous abordons la modélisation, l'analyse et le contrôle de la dynamique longitudinale de l'avion. Ensuite nous étendons certaines de ces études aux mouvements tridimensionnels d'avions au corps symétrique, tels que les missiles. Un résultat original de cette thèse est de préciser les conditions sur la force aérodynamique permettant de reformuler le problème du contrôle dans celui de la commande d'un corps sphérique, pour lequel des résultats de stabilité peuvent être démontrés. Les lois de commande proposées intègrent des termes intégraux et anti-wind up sans reposer sur une politique de commutation entre plusieurs lois de commande. / Over the last century, the scientific community has dealt with the control of flying machines by mainly developing different strategies in relation to different classes of aircraft, and no unified control approach has been developed so far. The present thesis contributes towards the development of a unified control approach for aerial vehicles by maintaining aerodynamic forces in the control design. It is assumed, however, that the aerodynamic effects of rotational and unsteady motions are negligible, and that the means of actuation for an aerial vehicle consist of a body-fixed thrust force for translational motion and a control torque for attitude monitoring. This thesis then focuses on the guidance loop of the control problem. One of the main objectives has been to determine how to regulate the thrust intensity and the vehicle orientation to compensate for the orientation-dependent external forces. In particular, the modeling, analysis, and control of the longitudinal aircraft dynamics is first addressed. Then, some of these studies are extended to three-dimensional motions of symmetric aircraft, such as missile-like bodies. An original outcome of this thesis is to state conditions on the aerodynamic force that allow the control problem to be recasted into that of controlling a spherical body. In this case, strong stability results can be shown. The proposed control laws incorporate integral and anti-wind up terms and do not rely on a switching policy between several control laws.