Predictive Modeling of Aircraft Dynamics

Training an encoder is provided. The method comprises inputting a current state of a number of aircraft into a recurrent layer of a neural network, wherein the current state comprises a reduced state in which a value of a specified parameter is missing. An action applied to the aircraft is input int...

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Bibliographic Details
Main Authors Soleyman, Sean, Hung, Fan Hin, Chen, Yang, Naderializadeh, Navid, Khosla, Deepak
Format Patent
LanguageEnglish
Published 29.12.2022
Subjects
AIRCRAFT
AVIATION
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COSMONAUTICS
COUNTING
DESIGNING, MANUFACTURING, ASSEMBLING, CLEANING, MAINTAINING ORREPAIRING AIRCRAFT, NOT OTHERWISE PROVIDED FOR
GROUND OR AIRCRAFT-CARRIER-DECK INSTALLATIONS SPECIALLYADAPTED FOR USE IN CONNECTION WITH AIRCRAFT
HANDLING, TRANSPORTING, TESTING OR INSPECTING AIRCRAFTCOMPONENTS, NOT OTHERWISE PROVIDED FOR
PERFORMING OPERATIONS
PHYSICS
TRANSPORTING
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Summary:Training an encoder is provided. The method comprises inputting a current state of a number of aircraft into a recurrent layer of a neural network, wherein the current state comprises a reduced state in which a value of a specified parameter is missing. An action applied to the aircraft is input into the recurrent layer concurrently with the current state. The recurrent layer learns a value for the parameter missing from current state, and the output of the recurrent layer is input into a number of fully connected hidden layers. The hidden layers, according to the current state, learned value, and current action, determine a residual output that comprises an incremental difference in the state of the aircraft resulting from the current action.
Bibliography:Application Number: US202217655468