EXTENDING THE ENDURANCE OF SMALL, VERTICAL TAKEOFF AND LANDING UNMANNED AERIAL SYSTEMS WITH THIN-FILM PHOTOVOLTAICS

Photovoltaic technology has advanced rapidly since its inception in the 1950s. Thin-film photovoltaics using heterojunction copper indium gallium diselenide (CIGS) material comprise lightweight, flexible solar cells that are well-suited for integration onto aircraft wing and horizontal surface areas. Small unmanned aerial systems (UASs) typically utilize electric propulsion sourced from lithium batteries. Extending the endurance of Department of Defense small UASs enhances mission capability and support to the warfighter; consequently, thin-film photovoltaic integration onto UASs has been well researched at the Naval Postgraduate School. This thesis extends previous research to examine photovoltaic integration on small UASs with vertical takeoff and landing (VTOL) capability. The Lockheed Martin Stalker VXE30 is a VTOL small UAS that was selected for analysis. Building a scaled CIGS array and power system allowed testing and extrapolation of data to analyze this platform in a variety of solar environments. MATLAB modeling allowed a comprehensive examination of performance data and demonstrated the efficacy of CIGS solar integration on VXE30 endurance.Distribution Statement A. Approved for public release: Distribution is unlimited.Lieutenant, United States Nav

A teleoperated unmanned rotorcraft flight test technique

NASA and the U.S. Army are jointly developing a teleoperated unmanned rotorcraft research platform at the National Aeronautics and Space Administration (NASA) Langley Research Center. This effort is intended to provide the rotorcraft research community an intermediate step between wind tunnel rotorcraft studies and full scale flight testing. The research vehicle is scaled such that it can be operated in the NASA Langley 14- by 22-Foot Subsonic Tunnel or be flown freely at an outside test range. This paper briefly describes the system's requirements and the techniques used to marry the various technologies present in the system to meet these requirements. The paper also discusses the status of the development effort

A Fuzzy Logic Approach for Separation Assurance and Collision Avoidance for Unmanned Aerial Systems

In the coming years, operations in low altitude airspace will vastly increase as the capabilities and applications of small Unmanned Aerial Systems (sUAS) continue to multiply. Therefore, solutions to managing sUAS in highly congested airspace must be explored. In this study, a Fuzzy Logic based approach was used to help mitigate the risk of collisions between aircraft using separation assurance and collision avoidance techniques. The system was evaluated for its effectiveness to mitigate the risk of mid-air collisions between aircraft. This system utilizes only current state information and can resolve potential conflicts without knowledge of intruder intent. The avoidance logic was verified using formal methods and shown to select the correct action in all instances. Additionally, the Fuzzy Logic Controllers were shown to always turn the vehicles in the correct direction. Numerical testing demonstrated that the avoidance system was able to prevent a mid-air collision between two sUAS in all tested cases. Simulations were also performed in a three-dimensional environment with a heterogenous fleet of sUAS performing a variety of realistic missions. Simulations showed that the system was 99.98 effective at preventing mid-air collisions when separation assurance was disabled (unmitigated case) and 100 effective when enabled (mitigated case)

System identification and model-based flight control system design for an agile maneuvring quadrotor platform

In this paper, we provide a system identification, model stitching and model-based flight control system design methodology for an agile maneuvering quadrotor micro aerial vehicle (MAV) technology demonstrator platform. The proposed MAV is designed to perform agile maneuvers in hover/low-speed and fast forward flight conditions in which significant changes in system dynamics are observed. As such, these significant changes result in considerable loss of performance and precision using classical hover or forward flight model based controller designs. To capture the changing dynamics, we consider an approach which is adapted from the full-scale manned aircraft and rotorcraft domain. Specifically, linear mathematical models of the MAV in hover and forward flight are obtained by using the frequency-domain system identification method and they are validated in time-domain. These point models are stitched with the trim data and quasi-nonlinear mathematical model is generated for simulation purposes. Identified linear models are used in a multi objective optimization based flight control system design approach in which several handling quality specifications are used to optimize the controller parameters. Lateral reposition and longitudinal depart/abort mission task elements from ADS-33E-PRF are scaled-down by using kinematic scaling to evaluate the proposed flight control systems. Position hold, trajectory tracking and aggressiveness analysis are performed, Monte-Carlo simulations and actual flight test results are compared. The results show that the proposed methodology provides high precision and predictable maneuvering control capability over an extensive speed envelope in comparison to classical control techniques. Our current work focuses on i) extension of the flight envelope of the mathematical model and ii) improvement of agile maneuvering capability of the MAV

Close Formation Flight Missions Using Vision-Based Position Detection System

In this thesis, a formation flight architecture is described along with the implementation and evaluation of a state-of-the-art vision-based algorithm for solving the problem of estimating and tracking a leader vehicle within a close-formation configuration. A vision-based algorithm that uses Darknet architecture and a formation flight control law to track and follow a leader with desired clearance in forward, lateral directions are developed and implemented. The architecture is run on a flight computer that handles the process in real-time while integrating navigation sensors and a stereo camera. Numerical simulations along with indoor and outdoor actual flight tests demonstrate the capabilities of detection and tracking by providing a low cost, compact size and low weight solution for the problem of estimating the location of other cooperative or non-cooperative flying vehicles within a formation architecture

Evaluation of the utility and performance of an autonomous surface vehicle for mobile monitoring of waterborne biochemical agents

Real-time water quality monitoring is crucial due to land utilization increases which can negatively impact aquatic ecosystems from surface water runoff. Conventional monitoring methodologies are laborious, expensive, and spatio-temporally limited. Autonomous surface vehicles (ASVs), equipped with sensors/instrumentation, serve as mobile sampling stations that reduce labor and enhance data resolution. However, ASV autopilot navigational accuracy is affected by environmental forces (wind, current, and waves) that can alter trajectories of planned paths and negatively affect spatio-temporal resolution of water quality data. This study demonstrated a commercially available solar powered ASV equipped with a multi-sensor payload ability to operate autonomously to accurately and repeatedly maintain established A-B line transects under varying environmental conditions, where lateral deviation from a planned linear route was measured and expressed as cross-track error (XTE). This work provides a framework for development of spatial/temporal resolution limitations of ASVs for real-time monitoring campaigns and future development of in-situ sampling technologies

Development of Cursor-on-Target Control for Semi-Autonomous Unmanned Aircraft Systems

The research presented in this thesis focuses on developing, demonstrating, and evaluating the concept of a Cursor-on-Target control system for semi-autonomous unmanned aircraft systems. The Department of Defense has mapped out a strategy in which unmanned aircraft systems will increasingly replace piloted aircraft. During most phases of flight autonomous unmanned aircraft control reduces operator workload, however, real-time information exchange often requires an operator to relay decision changes to the unmanned aircraft. The goal of this research is to develop a preliminary Cursor-on-Target control system to enable the operator to guide the unmanned aircraft with minimal workload during high task phases of flight and then evaluate the operator\u27s ability to conduct the mission using that control system. For this research, the problem of Cursor-on-Target control design has multiple components. Initially, a Cursor-on-Target controller is developed in Simulink. Then, this controller is integrated into the Aviator Visual Design Simulator to develop an operator-in-the-loop test platform. Finally, a ground target is simulated and tracked to validate the Cursor-on-Target controller. The Cursor-on-Target control system is then evaluated using a proposed operator rating scale

Design and Implementation of Intelligent Guidance Algorithms for UAV Mission Protection

In recent years, the interest of investigating intelligent systems for Unmanned Aerial Vehicles (UAVs) have increased in popularity due to their large range of capabilities such as on-line obstacle avoidance, autonomy, search and rescue, fast prototyping and integration in the National Air Space (NAS). Many research efforts currently focus on system robustness against uncertainties but do not consider the probability of readjusting tasks based on the remaining resources to successfully complete the mission. In this thesis, an intelligent algorithm approach is proposed along with decision-making capabilities to enhance UAVs post-failure performance. This intelligent algorithm integrates a set of path planning algorithms, a health monitoring system and a power estimation approach. Post-fault conditions are considered as unknown uncertainties that unmanned vehicles could encounter during regular operation missions. In this thesis, three main threats are studied: the presence of unknown obstacles in the environment, sub-system failures, and low power resources. A solution for adapting to new circumstances is addressed by enabling autonomous decision-making and re-planning capabilities in real time

Evaluation of Unmanned Aircraft Flying Qualities Using a Stitched Learjet Model

In recent years, military UAVs have taken over missions that were too dull, dirty, or dangerous for manned aircraft. The increased demand has led to a build-fly-fix-fly development mentality, plaguing the early lifecycle with staggering mishap rates. Currently, MIL-STD-1797 lists flying qualities for UAVs as TBD, and the standards for manned fixed wing are inadequate when applied to UAVs. In an effort to expand the database of UAV flying qualities, an analysis was completed on a Simulink model of an LJ-25D developed from Calspans Variable Stability System aircraft at the United States Test Pilot School. Three maneuvers were simulated: (1) a non-precision, non-aggressive climbing spiral, (2) a precision, non-aggressive side step landing, and (3) a precision, non-aggressive aerial refueling task. These maneuvers were chosen to evaluate the performance and workload of the aircraft as four stability and control parameters were scaled. The data were utilized in identifying trends between the scaled stability and control parameters and resulting workload and performance metrics. Thumbprint plots were generated to identify Level 1, Level 2, and Level 3 flying qualities and compared to MIL-STD-1797 plots. Results point to utilizing a combination of classical aircraft literal factors, such as ςsp and CAP, with newly developed mathematical techniques, such as L2 norm and TIC, to assess the workload of the flight controller and performance during the maneuver