Engineering Commons^™

Online Aircraft System Identification Using A Novel Parameter Informed Reinforcement Learning Method, Nathan Schaff

Doctoral Dissertations and Master's Theses

This thesis presents the development and analysis of a novel method for training reinforcement learning neural networks for online aircraft system identification of multiple similar linear systems, such as all fixed wing aircraft. This approach, termed Parameter Informed Reinforcement Learning (PIRL), dictates that reinforcement learning neural networks should be trained using input and output trajectory/history data as is convention; however, the PIRL method also includes any known and relevant aircraft parameters, such as airspeed, altitude, center of gravity location and/or others. Through this, the PIRL Agent is better suited to identify novel/test-set aircraft.

First, the PIRL method is applied to …

Novel 360-Degree Camera, Ian Gauger, Andrew Kurtz, Zakariya Niazi

Frameless

Circle Optics is developing novel technology for low-parallax, real time, panoramic image capture using an integrated array of multiple adjacent polygonal-edged cameras. This technology can be optimized and deployed for a variety of markets, including cinematic VR. Circle Optics’ existing prototype, Hydra Alpha, will be demonstrated.

Aessa Young Professionals Forum Webinar “Technologies And Skills That Will Gearup The Aerospace Industry Post Pandemic” - A Global Perspective With An Emphasis On South Africa October 2021, Linda Vee Weiland

Publications

A webinar presentation for AeSSA Young Professionals.

Plasma Aerodynamics: Experimental Quantification Of The Lift Force Generated On An Airfoil Using Plasma Actuation To Estimate Power Requirements In Small Uav Applications, Getachew Ashenafi

UNLV Theses, Dissertations, Professional Papers, and Capstones

This research addressed the amount of electric power required to induce specific changes in lift force using a NACA 2127 airfoil with a chord length of ~28 mm, connected to a micro load cell, in a wind tunnel of 103 square centimeter cross-section. A DBD plasma actuator supplied by a ZVS driven high voltage pulsed DC circuit, operating at a frequency of 17.4 kHz, was utilized for voltages of up to 5000 V. Two configurations of electrode gapping were compared to determine the efficient use of power. The configuration with a gap of ~1 mm between the upstream and downstream …

An Investigation Of The Use Of Cerium And Polyhedral Oligomeric Silsesquioxanes For The Protection Of Polymeric Epoxy Compounds In The Low Earth Orbit Environment, Jessica Miriam Piness

Dissertations

Low Earth orbit presents many hazards for composites including atomic oxygen, UV radiation, thermal cycling, micrometeoroids, and high energy protons. Atomic oxygen and vacuum ultraviolet radiation are of concern for space-bound polymeric materials as they degrade the polymers used as matrices for carbon fiber composites, which are used in satellites and space vehicles due to their high strength to weight ratios. Epoxy-amine thermosets comprise a common class of matrix due to processability and good thermal attributes. Polyhedral oligomeric silsesquioxanes (POSS) have shown the ability to reduce erosion in polyimides, polyurethanes, and other polymers when exposed to atomic oxygen. The POSS …

Quantum Computers Are Coming And Will Be Able To Solve Complex Aviation And Aerospace Problems, Nihad E. Daidzic

Aviation Department Publications

No abstract provided.

Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann M. Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito

Ole J Mengshoel

Investigations Of Synthetic Fuels: S8 And Sasol Ipk To Determine The Possibility Of Alternate Fuels In The Aerospace Industry, Scott M. Dyke

GS4 Georgia Southern Student Scholars Symposium

Investigations of Synthetic Fuels: S8 and Sasol IPK to Determine the Possibility of Operation as Alternate Fuels in the Aerospace Industry

Name: Scott Dyke

Co-Authors: Martin Muinos, Julia Heimberger, Dr. Valentin Soloiu,

An ever-growing society that becomes more and more dependent on a finite energy source will eventually exceed its supply. Fossil fuel quantities are continuously decreasing and new solutions are needed. According to the United States Department of Transportation, over 10 billion gallons of airline fuels have been consumed in each of the past 15 years with some years over 13 billion gallons. In the meantime, fuel costs have …

Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito

Ole J Mengshoel

Software Health Management With Bayesian Networks, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, Adnan Darwiche

Ole J Mengshoel

Multi-Focus And Multi-Level Techniques For Visualization And Analysis Of Networks With Thematic Data, Michele Cossalter, Ole J. Mengshoel, Ted Selker

Ole J Mengshoel

Software And System Health Management For Autonomous Robotics Missions, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel

Ole J Mengshoel

Advanced autonomous robotics space missions rely heavily on the flawless interaction of complex hardware, multiple sensors, and a mission-critical software system. This software system consists of an operating system, device drivers, controllers, and executives; recently highly complex AI-based autonomy software have also been introduced. Prior to launch, this software has to undergo rigorous verification and validation (V&V). Nevertheless, dormant software bugs, failing sensors, unexpected hardware-software interactions, and unanticipated environmental conditions—likely on a space exploration mission—can cause major software faults that can endanger the entire mission.

Our Integrated Software Health Management (ISWHM) system continuously monitors the hardware sensors and the software …

Bayesian Software Health Management For Aircraft Guidance, Navigation, And Control, Johann M. Schumann, Timmy Mbaya, Ole J. Mengshoel

Ole J Mengshoel

Modern aircraft — both piloted fly-by-wire commercial aircraft as well as UAVs — more and more depend on highly complex safety critical software systems with many sensors and computer-controlled actuators. Despite careful design and V&V of the software, severe incidents have happened due to malfunctioning software.

In this paper, we discuss the use of Bayesian networks to monitor the health of the on-board software and sensor system, and to perform advanced on-board diagnostic reasoning. We focus on the development of reliable and robust health models for combined software and sensor systems, with application to guidance, navigation, and control (GN&C). Our …

Integrating Probabilistic Reasoning And Statistical Quality Control Techniques For Fault Diagnosis In Hybrid Domains, Brian Ricks, Craig Harrison, Ole J. Mengshoel

Ole J Mengshoel

Software Health Management With Bayesian Networks, Ole J. Mengshoel, Johann M. Schumann

Ole J Mengshoel

No abstract provided.

Integrated Software And Sensor Health Management For Small Spacecraft, Johann Schumann, Ole J. Mengshoel, Timmy Mbaya

Ole J Mengshoel

Despite their size, small spacecraft have highly complex architectures with many sensors and computer-controlled actuators. At the same time, size, weight, and budget constraints often dictate that small spacecraft are designed as single-string systems, which means that there are no or few redundant systems. Thus, all components, including software, must operate as reliably. Faults, if present, must be detected as early as possible to enable (usually limited) forms of mitigation. Telemetry bandwidth for such spacecraft is usually very limited. Therefore, fault detection and diagnosis must be performed on-board. Further restrictions include low computational power and small memory.

In this paper, …

Probabilistic Model-Based Diagnosis: An Electrical Power System Case Study, Ole J. Mengshoel, Mark Chavira, Keith Cascio, Adnan Darwiche, Scott Poll, Serdar Uckun

Ole J Mengshoel

We present in this paper a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system (EPS), i.e., the Advanced Diagnstic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. Our probabilistic approach is formally well founded and based on Bayesian networks (BNs) and arithmetic circuits (ACs). We pay special attention to meeting two of the main challenges often associated with real-world application of model-based diagnosis technologies: model development and real-time reasoning. To address the challenge of model development, we develop a systematic approach to representing EPSs as BNs, …

Sensor Validation Using Bayesian Networks, Ole J. Mengshoel, Adnan Darwiche, Serdar Uckun

Ole J Mengshoel

One of NASA’s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation techniques address this problem: given a vector of sensor readings, decide whether sensors have failed, therefore producing bad data. We take in this paper a probabilistic approach, using Bayesian networks, to diagnosis and sensor validation, and investigate several relevant but slightly different Bayesian network queries. We emphasize that onboard inference can be performed on a …