Theory of Operation
The neural network of the IFCS learns flight characteristics in real time through the aircraft’s sensors and from error corrections from the primary flight computer, and then uses this information to create different flight characteristic models for the aircraft. The neural network only learns when the aircraft is in a stable flight condition, and will discard any characteristics that would cause the aircraft to go into a failure condition. If the aircraft’s condition changes from stable to failure, for example, if one of the control surfaces becomes damaged and unresponsive, the IFCS can detect this fault and switch the flight characteristic model for the aircraft. The neural network then works to drive the error between the reference model and the actual aircraft state to zero.
Read more about this topic: Intelligent Flight Control System
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