Abstract: A system and methods for life optimal power management of a distributed or centralized battery network system for use in aircraft functions and subsystems are disclosed. The method determines power priority of the subsystems, and selectively distributes power from the battery network system to the subsystems based on the power priority. Concurrently with distributing power, the method manages the energy in the battery network system. To determine whether the battery power is sufficient for aircraft functions, the method also computes and indicates the actual available energy left in the battery network systems. With this approach, the system and methods can provide a persistent power supply in the event an unexpected battery failure occurs, thereby enabling the aircraft to safely maintain flight operability despite a battery failure.

Abstract: Methods and systems for analyzing engine unbalance conditions are disclosed. In one embodiment, a method includes receiving vibrational data from a plurality of locations distributed over an engine and a surrounding engine support structure, and inputting the vibrational data into a neural network inverse model. The neural network inverse model establishes a relationship between the vibrational data and an unbalance condition of the engine, and outputs diagnostic information indicating the unbalance condition of the engine. In a further embodiment, a method further includes subjecting the vibrational data to a Fast Fourier Transformation to extract a desired once per revolution vibrational data prior to input to the neural network inverse model.

Abstract: Methods and systems for analyzing engine unbalance conditions are disclosed. In one embodiment, a method includes receiving vibrational data from a plurality of locations distributed over an engine and a surrounding engine support structure, and inputting the vibrational data into a neural network inverse model. The neural network inverse model establishes a relationship between the vibrational data and an unbalance condition of the engine, and outputs diagnostic information indicating the unbalance condition of the engine. In a further embodiment, a method further includes subjecting the vibrational data to a Fast Fourier Transformation to extract a desired once per revolution vibrational data prior to input to the neural network inverse model.

Abstract: Systems and methods for health data management are disclosed. In one embodiment, a method of monitoring health information for a multi-platform system includes receiving health information from one or more subsystems of a plurality of platforms, and analyzing the health information using one or more reasoner algorithms configured to predict a potential failure of the one or more subsystems. Upon prediction of a potential failure, the method includes providing a prognostic characteristic of the one or more subsystems. In alternate embodiments, the method may further include translating at least some of the health information for each of the one or more subsystems into a common format, and storing the translated health information into a database for subsequent analysis.

Abstract: Systems and methods for development testing of vehicles and components are disclosed. In one embodiment, a system includes a position reference system and a command and control architecture. The position reference system is configured to repetitively measure one or more position and motion characteristics of one or more vehicles operating within a control volume. The command and control architecture is configured to receive the repetitively measured characteristics from the position reference system, and to determine corresponding control signals based thereon. The control signals are then transmitted to the one or more vehicles to control at least one of position, movement, and stabilization of the one or more vehicles in a closed-loop feedback manner. The system may further include a health monitoring component configured to monitor health conditions of the one or more vehicles, the control signals being determined at least in part on the health conditions.

Abstract: Methods and systems for analyzing engine unbalance conditions are disclosed. In one embodiment, a method includes receiving vibrational data from a plurality of locations distributed over an engine and a surrounding engine support structure, and inputting the vibrational data into a neural network inverse model. The neural network inverse model establishes a relationship between the vibrational data and an unbalance condition of the engine, and outputs diagnostic information indicating the unbalance condition of the engine. In a further embodiment, a method further includes subjecting the vibrational data to a Fast Fourier Transformation to extract a desired once per revolution vibrational data prior to input to the neural network inverse model.

Abstract: A method, system and computer-readable medium for controlling a control subsystem of a vehicle. The control subsystem includes at least one propulsion, aerodynamic, or other control effector. The system also includes sensors for sensing vehicle position and motions and operating conditions, a control input device for generating control signals, and a generator for generating desired vehicle forces/moments from the sensed vehicle position and motions and operating conditions, and the generated control input signals based on predefined vehicle compensation and control laws. Also included is a neural network controller for generating control subsystem commands for the at least one propulsion, aerodynamic, or other control effector based on the generated desired forces/moments, wherein said neural network controller was trained based on pregenerated vehicle control distribution data. The neural network controller is also trained to compensate for one or more failed control effectors.

Abstract: A method and system for controlling a propulsion system of a vehicle. The propulsion system includes at least one propulsion effector. The system also includes sensors for sensing vehicle position and motions, a control device for generating control signals, and a generator for generating desired vehicle forces/moments from the sensed vehicle position and motions and the generated control signals based on predefined vehicle compensation and control laws. Also included is a neural network controller for generating propulsion commands for the at least one propulsion effector based on the generated desire forces/moments, wherein said neural network controller was trained based on pregenerated vehicle control distribution data.