Design and implementation of UAV performance validation system

Abstract. This thesis aims for design and implementation of a system for drone performance measurements, which can be used for validation of different drones for research projects accordingly. Additionally, the device should be able to be used as a part of a hardware-in-loop -system with simulators in drone research. The primary goal for this thesis is to build a system which helps to document different drone properties efficiently and safely. This is done with a system that consists of a robust frame, a force and torque measuring transducer, a drone stabilizing unit, a data logging system, and a remote-control power supply. For controlling the system, user interface was created to control the data stream, the drone stabilizing unit, and the power supply. This thesis includes a literature review of drone general classification properties and legal regulations. Short review of drone usage and selection criteria in industry and research is conducted, as well as in-depth review of the drone components and their relation to overall performance of the drone. The thesis also contains literature review of force and torque measuring theory, and other drone performance measuring units. The functionality of the designed unit is tested by building a drone from spare components, and valuating its performance based on e.g., lift generation, power consumption and visual behavior of the drone. Measured data is documented, and with the documents, drone’s suitability for future research projects can be assessed. According to the results, the unit can be used to evaluate drone’s performance, and groundwork for Hardware-in-loop simulator connection for drone research. The testing unit and the data recordings as well as the built testing drone stays within the research facility for further development.UAV testausjärjestelmän suunnittelu ja toteutus. Tiivistelmä. Tässä diplomityössä suunnitellaan ja valmistetaan droonien suorituskykyä mittaava tutkimuslaitteisto, jonka avulla voidaan arvioida erilaisten droonien soveltuvuutta tutkimusprojekteihin tapauskohtaisesti. Työssä tavoitellaan helppokäyttöistä järjestelmää, jonka avulla itse tehtyjen droonien ominaisuuksia voidaan dokumentoida turvallisesti ja tehokkaasti. Työssä perehdytään droonien luokitteluun tutustumalla voimassa oleviin säädöksiin, sekä droonin suorituskykyä kuvaaviin ominaisuuksiin. Työssä tarkastellaan droonien käyttöä eri aloilla arvioiden esiin nousseita droonin valintaperusteita ja ominaisuuksia. Tämän jälkeen tutustutaan droonien rakenteeseen ja ominaisuuksiin. Voiman mittauksen teoriaan sekä kehitettyihin mittausmenetelmiin tutustutaan tukemaan anturivalintaa. Suunniteltu järjestelmä koostuu tukevasta rungosta, voiman mittaukseen soveltuvasta anturista, droonin vakauttamisen kokonaisuudesta, datan keräysjärjestelmästä sekä etäohjattavasta virtalähteestä. Laitteiston ohjaukseen luotiin rajapinta, jonka kautta järjestelmää voidaan hallita. Järjestelmän toimivuus todettiin kahdella mittauskäyttöön soveltuvalla droonilla, joiden suorituskykyä arvioitiin droonien ominaisuuksien, sekä visuaalisen käyttäytymisen avulla. Mittauksien tulokset dokumentoitiin, ja dokumentaation perusteella voidaan arvioida sekä tutkimuslaitteiston toimivuutta, että mitattujen droonien soveltuvuutta tulevissa tutkimusprojekteissa. Mittausten perusteella voidaan todeta laitteen soveltuvan droonien suorituskyvyn mittaamiseen, sekä pohjatyöksi simulaattorikytkentään. Mittalaitteisto sekä mittaustulokset jäävät Biomimetiikka ja älykkäät järjestelmät -tutkimusyksikön käyttöön droonitutkimuksen tueksi

Addressing Complexity and Intelligence in Systems Dependability Evaluation

Engineering and computing systems are increasingly complex, intelligent, and open adaptive. When it comes to the dependability evaluation of such systems, there are certain challenges posed by the characteristics of “complexity” and “intelligence”. The first aspect of complexity is the dependability modelling of large systems with many interconnected components and dynamic behaviours such as Priority, Sequencing and Repairs. To address this, the thesis proposes a novel hierarchical solution to dynamic fault tree analysis using Semi-Markov Processes. A second aspect of complexity is the environmental conditions that may impact dependability and their modelling. For instance, weather and logistics can influence maintenance actions and hence dependability of an offshore wind farm. The thesis proposes a semi-Markov-based maintenance model called “Butterfly Maintenance Model (BMM)” to model this complexity and accommodate it in dependability evaluation. A third aspect of complexity is the open nature of system of systems like swarms of drones which makes complete design-time dependability analysis infeasible. To address this aspect, the thesis proposes a dynamic dependability evaluation method using Fault Trees and Markov-Models at runtime.The challenge of “intelligence” arises because Machine Learning (ML) components do not exhibit programmed behaviour; their behaviour is learned from data. However, in traditional dependability analysis, systems are assumed to be programmed or designed. When a system has learned from data, then a distributional shift of operational data from training data may cause ML to behave incorrectly, e.g., misclassify objects. To address this, a new approach called SafeML is developed that uses statistical distance measures for monitoring the performance of ML against such distributional shifts. The thesis develops the proposed models, and evaluates them on case studies, highlighting improvements to the state-of-the-art, limitations and future work

Source term estimation of a hazardous airborne release using an unmanned aerial vehicle

Gaining information about an unknown gas source is a task of great importance with applications in several areas including: responding to gas leaks or suspicious smells, quantifying sources of emissions, or in an emergency response to an industrial accident or act of terrorism. In this paper, a method to estimate the source term of a gaseous release using measurements of concentration obtained from an unmanned aerial vehicle (UAV) is described. The source term parameters estimated include the three dimensional location of the release, its emission rate, and other important variables needed to forecast the spread of the gas using an atmospheric transport and dispersion model. The parameters of the source are estimated by fusing concentration observations from a gas detector on-board the aircraft, with meteorological data and an appropriate model of dispersion. Two models are compared in this paper, both derived from analytical solutions to the advection diffusion equation. Bayes’ theorem, implemented using a sequential Monte Carlo algorithm, is used to estimate the source parameters in order to take into account the large uncertainties in the observations and formulated models. The system is verified with novel, outdoor, fully automated experiments, where observations from the UAV are used to estimate the parameters of a diffusive source. The estimation performance of the algorithm is assessed subject to various flight path configurations and wind speeds. Observations and lessons learned during these unique experiments are discussed and areas for future research are identified

INSPIRE Newsletter Spring 2022

https://scholarsmine.mst.edu/inspire-newsletters/1010/thumbnail.jp

Energy Neutral Design of Embedded Systems for Resource Constrained Monitoring Applications

Automatic monitoring of environments, resouces and human processes are crucial and foundamental tasks to improve people's quality of life and to safeguard the natural environment. Today, new technologies give us the possibility to shape a greener and safer future. The more specialized is the kind of monitoring we want to achieve, more tight are the constraints in terms of reliability, low energy and maintenance-free autonomy. The challenge in case of tight energy constraints is to find new techniques to save as much power as possible or to retrieve it from the very same environment where the system operates, towards the realization of energy neutral embedded monitoring systems. Energy efficiency and battery autonomy of such devices are still the major problem impacting reliability and penetration of such systems in risk-related activities of our daily life. Energy management must not be optimized to the detriment of the quality of monitoring and sensors can not be operated without supply. In this thesis, I present different embedded system designs to bridge this gap, both from the hardware and software sides, considering specific resource constrained scenarios as case studies that have been used to develop solutions with much broader validity. Results achieved demonstrate that energy neutrality in monitoring under resource constrained conditions can be obtained without compromising efficiency and reliability of the outcomes

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challengespublishersversionPeer reviewe

Fault Tolerant Flight Control of Unmanned Aerial Vehicles

Safety, reliability and acceptable level of performance of dynamic control systems are the major keys in all control systems especially in safety-critical control systems. A controller should be capable of handling noises and uncertainties imposed to the controlled process. A fault-tolerant controller should be able to control a system with guaranteed stability and good or acceptable performance not only in normal operation conditions but also in the presence of partial faults or total failures that can be occurred in the components of the system. When a fault occurs in a system, it suddenly starts to behave in an unanticipated manner. Thereby, a fault-tolerant controller should be designed for being able to handle the fault and guarantee system stability and acceptable performance in the presence of faults/damages. This shows the importance and necessity of Fault-Tolerant Control (FTC) to safety-critical and even nowadays for some new and non-safety-critical systems. During recent years, Unmanned Aerial Vehicles (UAVs) have proved to play a significant role in military and civil applications. The success of UAVs in different missions guarantees the growing number of UAVs to be considerable in future. Reliability of UAVs and their components against faults and failures is one of the most important objectives for safety-critical systems including manned airplanes and UAVs. The reliability importance of UAVs is implied in the acknowledgement of the Office of the Secretary of Defense in the UAV Roadmap 2005-2030 by stating that, ”Improving UA [unmanned aircraft] reliability is the single most immediate and long-reaching need to ensure their success”. This statement gives a wide future scenery of safety, reliability and Fault-Tolerant Flight Control (FTFC) systems of UAVs. The main objective of this thesis is to investigate and compare some aspects of fault tolerant flight control techniques such as performance, robustness and capability of handling the faults and failures during the flight of UAVs. Several control techniques have been developed and tested on two main platforms at Concordia University for fault-tolerant control techniques development, implementation and flight test purposes: quadrotor and fixedwing UAVs. The FTC techniques developed are: Gain-Scheduled Proportional-Integral-Derivative (GS-PID), Control Allocation and Re-allocation (CA/RA), Model Reference Adaptive Control (MRAC), and finally the Linear Parameter Varying (LPV) control as an alternative and theoretically more comprehensive gain scheduling based control technique. The LPV technique is used to control the quadrotor helicopter for fault-free conditions. Also a GS-PID controller is used as a fault-tolerant controller and implemented on a fixedwing UAV in the presence of a stuck rudder failure case