Die Energieversorgung unbemannter Flugobjekte (UAV) erfolgt gegenwärtig über Batterie-Module. Diese sind als zusätzliche Bauteile in die Struktur eingebracht. Daher erhöht sich das Gesamtgewicht der Struktur deutlich. Im Sinne der Energiespeicherung existieren verschiedene multifunktionale Konzeptansätze. Hierunter zählen strukturelle, elektrische Energiespeicherungssysteme (SEES). Bei diesen Konzepten erfolgt die Energiespeicherung in den Bauteilen bei gleichzeitiger Erfüllung struktureller Eigenschaften. Somit gelten diese als masselose Energiespeicherungssysteme. Im Rahmen dieser Thesis erfolgt eine Betrachtung verschiedener SEES. Schließlich werden strukturelle Superkondensatoren (SSC) zur Integration in ein UAV ausgewählt. Als Integrationsobjekt dient die Drohne DJI Matrice 600 Pro. Ein SSC mit besten Eigenschaften wird anhand einer systematischen Methode aus der aktuellen Literatur ermittelt. Dieser Favorit wird konzeptionell in die Drohne integriert. Diesbezüglich erfolgen verschiedene, physikalische Berechnungen zu elektrischen Eigenschaften und anliegenden Kräften, sodass Rückschlüsse zur Leistungsfähigkeit getroffen werden können. Im weiteren Verlauf wird eine Mehrkörpersimulation mit der Finite-Elemente-Methode (FEM) am Untersuchungsobjekt durchgeführt. Mit der Kenntnis über die anliegenden Beanspruchungen erfolgt weiterführend eine detailgetreue, strukturmechanische Analyse des SSC unter Verwendung der FEM an repräsentativen Volumenelementen. Fortan wird das multiphysikalische Kopplungsphänomen im strukturellen Elektrolyten simuliert. Hierfür werden mathematische Abhängigkeiten von mechanischen Einwirkungen auf geometrisch, veränderliche Größen ermittelt. Diese werden in eine elektrochemische Simulation überführt, sodass das multiphysikalische Kopplungsphänomen berechnet wird. Als Ergebnis zeigt sich, dass die Kompression des Elektrolyten negative Auswirkungen auf die elektrochemischen Eigenschaften hat...:Symbol- und Abkürzungsverzeichnis Abbildungsverzeichnis Tabellenverzeichnis 1 Einleitung 2 Grundlagen 2.1 Strukturelle elektrische Energiespeicherungssysteme 2.2 Superkondensatoren – Aufbau und Funktionsweise 2.3 Berechnungsgrößen am strukturellen Superkondensator 3 Stand der Forschung 3.1 Literaturrecherche – Strukturelle Superkondensatoren 3.2 Festlegung von Parametern und Auswahl des SSC 4 Anwendungsfall: DJI Matrice 600 Pro 4.1 Produktanalyse DJI Matrice 600 Pro 4.2 Integration des strukturellen Superkondensators in die Struktur 4.3 Berechnung elektrischer Eigenschaften 4.4 Analyse und Berechnung der wirkenden Kräfte 4.5 FEM-Mehrkörpersimulation am UAV-Anwendungsfall 5 Strukturmechanische Simulation am SSC 5.1 SSC-Bereichsanalyse und Simulationsaufgabe 5.2 Repräsentative Volumenelemente und Einheitszelle 5.3 Simulation Bereich 1: Poröse Faser in der Matrix 5.4 Simulation Bereich 2: Fasern in der Matrix 5.5 Simulation Bereich 3: Poröser Elektrolyt 6 Multiphysikalische SSC-Simulation 6.1 Multiphysikalischer Kopplungseffekt 6.2 Analyse der geometrischen Größen Porosität und Tortuosität 6.3 Multiphysikalische Simulation mit COMSOL Multiphysics Zusammenfassung und Ausblick Literatur / Unmanned aerial vehicles (UAV) are currently powered by batteries, which are integrated as additional components within their structure. However, the substantial weight of these batteries leads to increased energy consumption and reduced flight time. In addition to battery-based energy systems, there are alternative concepts that serve multifunctional roles. Structural electrical energy storage systems (SEES) for example carry loads and offer electrical energy storage functions at the same time. In this work, structural Supercapacitors (SSC) are selected as SEES candidates. A systematic approach is employed to integrate an SSC into the DJI Matrice 600 Pro done as an UAV use case. The efficiency of the integrated system is assessed through various physical calculations. Subsequently, a multi-body simulation using the finite element method is conducted on the chosen UAV model. Furthermore, representative volume elements are defined within the structural supercapacitor, and simulations are performed to comprehend the underlying processes. During the exploration of multiphysical coupling effects between mechanical stresses and electrochemical behaviors, certain geometric parameters are identified as influential factors. Regression analysis is employed to formulate mathematical equations representing these dependencies for simulation purposes. A multiphysical simulation is executed, considering compression as a representative load case. The results are evaluated using cyclic voltammetry. The study concludes that mechanical compression loads have an adverse effect on the electrochemical properties of the structural supercapacitor:Symbol- und Abkürzungsverzeichnis Abbildungsverzeichnis Tabellenverzeichnis 1 Einleitung 2 Grundlagen 2.1 Strukturelle elektrische Energiespeicherungssysteme 2.2 Superkondensatoren – Aufbau und Funktionsweise 2.3 Berechnungsgrößen am strukturellen Superkondensator 3 Stand der Forschung 3.1 Literaturrecherche – Strukturelle Superkondensatoren 3.2 Festlegung von Parametern und Auswahl des SSC 4 Anwendungsfall: DJI Matrice 600 Pro 4.1 Produktanalyse DJI Matrice 600 Pro 4.2 Integration des strukturellen Superkondensators in die Struktur 4.3 Berechnung elektrischer Eigenschaften 4.4 Analyse und Berechnung der wirkenden Kräfte 4.5 FEM-Mehrkörpersimulation am UAV-Anwendungsfall 5 Strukturmechanische Simulation am SSC 5.1 SSC-Bereichsanalyse und Simulationsaufgabe 5.2 Repräsentative Volumenelemente und Einheitszelle 5.3 Simulation Bereich 1: Poröse Faser in der Matrix 5.4 Simulation Bereich 2: Fasern in der Matrix 5.5 Simulation Bereich 3: Poröser Elektrolyt 6 Multiphysikalische SSC-Simulation 6.1 Multiphysikalischer Kopplungseffekt 6.2 Analyse der geometrischen Größen Porosität und Tortuosität 6.3 Multiphysikalische Simulation mit COMSOL Multiphysics Zusammenfassung und Ausblick Literatur

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

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Cyber-physical systems (CPSs) are systems that integrate physical elements with a cyber layer that enables sensing, monitoring, and processing the data from the physical components. Examples of CPSs include autonomous vehicles, unmanned aerial vehicles (UAVs), smart grids, and the Internet of Things (IoT). In particular, many critical infrastructure (CI) that are vital to our modern day cities and communities, are CPSs. This wide range of CPSs domains represents a cornerstone of smart cities in which various CPSs are connected to provide efficient services. However, this level of connectivity has brought forward new security challenges and has left CPSs vulnerable to many cyber-physical attacks and disruptive events that can utilize the cyber layer to cause damage to both cyber and physical components. Addressing these security and operation challenges requires developing new security solutions to prevent and mitigate the effects of cyber and physical attacks as well as improving the CPSs response in face of disruptive events, which is known as the CPS resilience. To this end, the primary goal of this dissertation is to develop novel analytical tools that can be used to study, analyze, and optimize the resilience and security of critical CPSs. In particular, this dissertation presents a number of key contributions that pertain to the security and the resilience of multiple CPSs that include power systems, the Internet of Things (IoT), UAVs, and transportation networks. First, a mathematical framework is proposed to analyze and mitigate the effects of GPS spoofing attacks against UAVs. The proposed framework uses system dynamics to model the optimal routes which UAVs can follow in normal operations and under GPS spoofing attacks. A countermeasure mechanism, built on the premise of cooperative localization, is then developed to mitigate the effects of these GPS spoofing attacks. To practically deploy the proposed defense mechanism, a dynamic Stackelberg game is formulated to model the interactions between a GPS spoofer and a drone operator. The equilibrium strategies of the game are analytically characterized and studied through a novel, computationally efficient algorithm. Simulation results show that, when combined with the Stackelberg strategies, the proposed defense mechanism will outperform baseline strategy selection techniques in terms of reducing the possibility of UAV capture. Next, a game-theoretic framework is developed to model a novel moving target defense (MTD) mechanism that enables CPSs to randomize their configurations to proactive deter impending attacks. By adopting an MTD approach, a CPS can enhance its security against potential attacks by increasing the uncertainty on the attacker. The equilibrium of the developed single-controller, stochastic MTD game is then analyzed. Simulation results show that the proposed framework can significantly improve the overall utility of the defender. Third, the concept of MTD is coupled with new cryptographic algorithms for enhancing the security of an mHealth Internet of Things (IoT) system. In particular, using a combination of theory and implementation, a framework is introduced to enable the IoT devices to update their cryptographic keys locally to eliminate the risk of being revealed while they are shared. Considering the resilience of CPSs, a novel framework for analyzing the component- and system-level resilience of CIs is proposed. This framework brings together new ideas from Bayesian networks and contract theory – a Nobel prize winning theory – to define a concrete system-level resilience index for CIs and to optimize the allocation of resources, such as redundant components, monitoring devices, or UAVs to help those CIs improve their resilience. In particular, the developed resilience index is able to account for the effect of CI components on the its probability of failure. Meanwhile, using contract theory, a comprehensive resource allocation framework is proposed enabling the system operator to optimally allocate resources to each individual CI based on its economic contribution to the entire system. Simulation results show that the system operator can economically benefit from allocating the resources while dams can have a significant improvement in their resilience indices. Subsequently, the developed contract-theoretic framework is extended to account for cases of asymmetric information in which the system operator has only partial information about the CIs being in some vulnerability and criticality levels. Under such asymmetry, it is shown that the proposed approach maximizes the system operator's utility while ensuring that no CI has an incentive to ask for another contract. Next, a proof-of-concept framework is introduced to analyze and improve the resilience of transportation networks against flooding. The effect of flooding on road capacities and on the free-flow travel time, is considered for different rain intensities and roads preparedness. Meanwhile, the total system's travel time before and after flooding is evaluated using the concept of a Wardrop equilibrium. To this end, a proactive mechanism is developed to reduce the system's travel time, after flooding, by shifting capacities (available lanes) between same road sides. In a nutshell, this dissertation provides a suite of analytical techniques that allow the optimization of security and resilience across multiple CPSs. / Doctor of Philosophy / Cyber-physical systems (CPSs) have recently been used in many application domains because of their ability to integrate physical elements with a cyber layer allowing for sensing, monitoring, and remote controlling. This pervasive use of CPSs in different applications has brought forward new security challenges and threats. Malicious attacks can now leverage the connectivity of the cyber layer to launch remote attacks and cause damage to the physical components. Taking these threats into consideration, it became imperative to ensure the security of CPSs. Given that many CPSs provide critical services, for instance many critical infrastructure (CI) are CPSs such as smart girds and nuclear reactors; it is then inevitable to ensure that these critical CPSs can maintain proper operation. One key measure of the CPS’s functionality, is resilience which evaluates the ability of a CPS to deliver its designated service under potentially disruptive situations. In general, resilience measures a CPS’s ability to adapt or rapidly recover from disruptive events. Therefore, it is crucial for CPSs to be resilient in face of potential failures. To this end, the central goal of this dissertation is to develop novel analytical frameworks that can evaluate and improve security and resilience of CPSs. In these frameworks, cross-disciplinary tools are used from game theory, contract theory, and optimization to develop robust analytical solutions for security and resilience problems. In particular, these frameworks led to the following key contributions in cyber security: developing an analytical framework to mitigate the effects of GPS spoofing attacks against UAVs, introducing a game-theoretic moving target defense (MTD) framework to improve the cyber security, and securing data privacy in m-health Internet of Things (IoT) networks using a MTD cryptographic framework. In addition, the dissertation led to the following contributions in CI resilience: developing a general framework using Bayesian Networks to evaluate and improve the resilience of CIs against their components failure, introducing a contract-theoretic model to allocate resources to multiple connected CIs under complete and asymmetric information scenarios, providing a proactive plan to improve the resilience of transportation networks against flooding, and, finally, developing an environment-aware framework to deploy UAVs in disaster-areas.

Advances in mobile robot technology allow an increasing variety of applications to be imagined, including: search and rescue, exploration of unknown areas and working with hazardous materials. State of the art robots are able to behave autonomously and without direct human control, using on-board devices to perceive, navigate and reason about the world. Unmanned Aerial Vehicles (UAVs) are particularly well suited to performing advanced sensing tasks by moving rapidly through the environment irrespective of the terrain. Deploying groups of mobile robots offers advantages, such as robustness to individual failures and a reduction in task completion time. However, to operate efficiently these teams require specific approaches to enable the individual agents to cooperate. This thesis proposes coordinated approaches to search scenarios for teams of UAVs. The primary application considered is Wilderness Search and Rescue (WiSaR), although the techniques developed are applicable elsewhere. A novel frontier-based search approach is developed for rotor-craft UAVs, taking advantage of available terrain information to minimise altitude changes during flight. This is accompanied by a lightweight coordination mechanism to enable cooperative behaviour with minimal additional overhead. The concept of a team rendezvous is introduced, at which all team members attend to exchange data. This also provides an ideal opportunity to create a comprehensive team solution to relay newly gathered data to a base station. Furthermore, the delay between sensing and the acquired data becoming available to mission commanders is analysed and a technique proposed for adapting the team to meet a latency requirement. These approaches are evaluated and characterised experimentally through simulation. Coordinated frontier search is shown to outperform greedy walk methods, reducing redundant sensing coverage using only a minimal coordination protocol. Combining the search, rendezvous and relay techniques provides a holistic approach to the deployment of UAV teams, meeting mission objectives without extensive pre-configuration.

Thesis (PhD (Electrical and Electronic Engineering))--Stellenbosch University, 2008. / A strategy for the design of an effective, practically feasible, robust, computationally efficient autopilot for three dimensional manoeuvre flight control of Unmanned Aerial Vehicles is presented. The core feature of the strategy is the design of attitude independent inner loop acceleration controllers. With these controllers implemented, the aircraft is reduced to a point mass with a steerable acceleration vector when viewed from an outer loop guidance perspective. Trajectory generation is also simplified with reference trajectories only required to be kinematically feasible. Robustness is achieved through uncertainty encapsulation and disturbance rejection at an acceleration level. The detailed design and associated analysis of the inner loop acceleration controllers is carried out for the case where the airflow incidence angles are small. For this case it is shown that under mild practically feasible conditions the inner loop dynamics decouple and become linear, thereby allowing the derivation of closed form pole placement solutions. Dimensional and normalised non-dimensional time variants of the inner loop controllers are designed and their respective advantages highlighted. Pole placement constraints that arise due to the typically weak non-minimum phase nature of aircraft dynamics are developed. A generic, aircraft independent guidance control algorithm, well suited for use with the inner loop acceleration controllers, is also presented. The guidance algorithm regulates the aircraft about a kinematically feasible reference trajectory. A number of fundamental basis trajectories are presented which are easily linkable to form complex three dimensional manoeuvres. Results from simulations with a number of different aircraft and reference trajectories illustrate the versatility and functionality of the autopilot. Key words: Aircraft control, Autonomous vehicles, UAV flight control, Acceleration control, Aircraft guidance, Trajectory tracking, Manoeuvre flight control.

The focus of this thesis is on Actual Entities, a concept created by the philosopher Alfred North Whitehead, and how the concept can be applied to Unmanned Aerial Vehicles as a behavioral control method. Actual Entities are vector based, atomic units that use a method called prehension to observe their environment and react with various actions. When combining multiple Actual Entities a Colony of Prehending Entities is created; when observing their prehensions an intelligent behavior emerges. By applying the characteristics of Actual Entities to Unmanned Aerial Vehicles, specifically in a situation where they are searching for targets, this emergent, intelligent behavior can be seen as they search a designated area and locate specified targets. They will alter their movements based on the prehensions of the environment, surrounding Unmanned Aerial Vehicles, and targets.

M.Ing. / Linear control system theory is well developed and has lead to a number of control system types with well-defined design methods that can be applied to any linear system. Unfortunately, no system in nature is truly linear. As a result, such non-linear systems must be represented by a linear model that is accurate over some region of the operating states of the system. The success of linear control theory in commercial applications is testament to the fact that some types of systems can be adequately represented by a linear model. However, systems with time-varying dynamics or non-linearities such as input or operating state saturation cannot always be adequately controlled by linear control systems. For that reason, non-linear control techniques must be investigated. This project aims to investigate Non-linear Model Predictive Control theory and practical implementation in the context of developing an autopilot for an Unmanned Aerial Vehicle based on a miniature helicopter. A non-linear model of the dynamics of an X-Cell Spectra G radio-controlled helicopter was developed based on the existing literature. A number of experiments were performed to determine the parameters of this model. Significant future work exists in designing additional ground experiments since certain parameters are difficult to measure safely in the laboratory. Additional work to improve the accuracy of the model at high airspeeds, as well as incorporating a more accurate yaw dynamics model, is also required. Following this, a Non-linear Model Predictive Control autopilot was simulated using MATLAB®. The simulation tested the effects of control system parameters such as control horizon and sampling period, as well as the sensor noise susceptibility and its ability to handle wind as a random disturbance. The results determined adequate control system parameters for level flight as well as landing the helicopter under ideal conditions. Simulations in which sensor noise and wind were added showed that the control system is significantly affected by sensor noise and that it cannot hover in the presence of wind. A real-time implementation was not achieved during this work; however, several directions for future research have been discussed.

The highly optimized performance of nature’s creations and biological assemblies has inspired the development of their engineered counter parts that can potentially outperform conventional systems. In particular, bat wings are populated with air flow hair receptors which feedback the information about airflow over their surfaces for enhanced stability and maneuverability during their flight. The hairs in the bat wing membrane play a role in the maneuverability tasks, especially during low-speed flight. The developments of artificial hair sensors (AHS) are inspired by biological hair cells in aerodynamic feedback control designs. Current mathematical models for hair receptors are limited by strict simplifying assumptions of creeping flow hair Reynolds number on AHS fluid-structure interaction (FSI), which may be violated for hair structures integrated on small-scaled Unmanned Aerial Vehicles (UAVs). This study motivates by an outstanding need to understand the dynamic response of hair receptors in flow regimes relevant to bat-scaled UAVs. The dynamic response of the hair receptor within the creeping flow environment is investigated at distinct freestream velocities to extend the applicability of AHS to a wider range of low Reynolds number platforms. Therefore, a threedimensional FSI model coupled with a finite element model using the computational fluid dynamics (CFD) is developed for a hair-structure and multiple hair-structures in the airflow. The Navier-Stokes equations including continuity equation are solved numerically for the CFD model. The grid independence of the FSI solution is studied from the simulations of the hairstructure mesh and flow mesh around the hair sensor. To describe the dynamic response of the hair receptors, the natural frequencies and mode shapes of the hair receptors, computed from the finite element model, are compared with the excitation frequencies in vacuum. This model is described with both the boundary layer effects and effects of inertial forces due to fluid-structure xiv interaction of the hair receptors. For supporting the FSI model, the dynamic response of the hair receptor is also validated considering the Euler-Bernoulli beam theory including the steady and unsteady airflow.