Operations Research, Systems Engineering and Industrial Engineering Commons^™

An Online Adaptive Machine Learning Framework For Autonomous Fault Detection, Nolan Coulter

Doctoral Dissertations and Master's Theses

The increasing complexity and autonomy of modern systems, particularly in the aerospace industry, demand robust and adaptive fault detection and health management solutions. The development of a data-driven fault detection system that can adapt to varying conditions and system changes is critical to the performance, safety, and reliability of these systems. This dissertation presents a novel fault detection approach based on the integration of the artificial immune system (AIS) paradigm and Online Support Vector Machines (OSVM). Together, these algorithms create the Artificial Immune System augemented Online Support Vector Machine (AISOSVM).

The AISOSVM framework combines the strengths of the AIS and …

Airspace Integration Of New Entrants And Safety Risk Management Models, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

In recent years, the demand for airspace access of Unmanned Aerial Systems (UAS) increased significantly and is continuously increasing for different altitude-types UAS. A similar evolution is expected from Commercial Space Operations (CSO) in the next years. These aviation/aerospace systems will need to be seamlessly integrated into the National Airspace System (NAS), at their operational altitude levels, and accounted for from all perspectives, including proactively addressing their safety hazards. This thesis captures the requirements for the new entrants’ integration, and then identifies and analyzes the safety risks added to the NAS operations by its new entrants, the future omnipresent UAS …

The Effect Of Task Load, Automation Reliability, And Environment Complexity On Uav Supervisory Control Performance, Sarah M. Sherwood

Doctoral Dissertations and Master's Theses

Over the last decade, military unmanned aerial vehicles (UAVs) have experienced exponential growth and now comprise over 40% of military aircraft. However, since most military UAVs require multiple operators (usually an air vehicle operator, payload operator, and mission commander), the proliferation of UAVs has created a manpower burden within the U.S. military. Fortunately, simultaneous advances in UAV automation have enabled a switch from direct control to supervisory control; future UAV operators will no longer directly control a single UAV subsystem but, rather, will control multiple advanced, highly autonomous UAVs. However, research is needed to better understand operator performance in a …