Self-Aware Aerospace Vehicle Contingency Management

Aurora Flight Sciences, with Agent Oriented Software, proposes to develop a contingency management system that dynamically performs decision-making based on both sensed and predictive information to carry out adaptive missions and maintenance. This system will mirror the human nervous system, having sensing capabilities distributed throughout systems and subsystems measuring characteristics that predict the conditional response of the aerospace vehicle. The vehicle 'nervous system' of embedded distributed sensors and reasoning agents will generate real-time information on vehicle condition. Like a nervous system, each subsystem will communicate with a higher-level system-reasoning agent. The central reasoning agent will manage mission control systems to perform adaptive maneuvers informed by this network of sensors.This program will concentrate on the composite airframe structure as the system of interest and will encompass the following areas:1. Assignment of airframe capability figures to maneuvering limits (i.e. various maneuvers that load the airframe, coupled with the capability of the airframe to take that loading).2. Analysis of available inputs including the environment (temperature, altitude, humidity), the structural state (damage type, size and location), and the loading (inertia, pressure profiles).3. Creation of an algorithm to determine the capability of the airframe, and potentially return the viability of performing different maneuvers. A safety factor may also be returned, which could be used to determine alternate safe maneuvers.4. Mission decisions based on whether the airframe can safely perform the required maneuvers, and if not, what maneuvers can be performed that would still enable it to satisfy the mission.