Input output vectors for adaptive learning stabilizer

It would be useful if the arducopter gurus help me to understand the input parameters to NN i.e. the configuration of the copter while in flight, my understanding:

Assumption: desired Roll, Pitch and Yaw to be 0 radians and height H fixed. Not worrying about drift for this example. No external force e.g. wind. Payload might not be at GC. Actuation numbers are deltas + or -

Input:

1. 3 angles: Roll, Pitch and Yaw

2. 4 speeds for 4 motors 

3. height 

Output 

1. 3 actuation numbers for Roll, Pitch and Yaw

2. 4 speeds for 4 motors 

3. Thrust actuation number

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  • From Birol the developer for FNNTOOl, I think he is a brilliant person to join us here:

    time now = tn

    Speed of Motor  = Sm ( eg Sm1 Speed of Motor 1)

    Delta Roll = Dr = Roll( tn ) - Roll ( desired )

    Delta Pitch = Dp= Pitch ( tn ) -  Pitch ( desired )

    Delta Yaw = Dy=  Yaw ( tn ) - Yaw ( desired )

    Error Roll =  Er = Roll ( desired  ) - Roll (tn-1)

    Error  Pitch =  Ep =  Pitch ( desired ) -  Pitch (tn-1)

    Error Yaw =  Ey = Yaw ( desired ) - Yaw (tn-1)

    Inputs :  Dr ,Dp,Dy,Er,Ep,Ey,Sm1,Sm2,Sm3,Sm4

    Outputs : Sm1 (tn+1) , Sm2 (tn+1) , Sm3  (tn+1) , Sm4 (tn+1)

    1.  if( first run  )  initial errors zero
    2. else Calculate Errors of Roll, Pitch and Yaw from ( tn-1 values)
    3. get desired Roll, Pitch and Yaw
    4. read  actual Roll, Pitch and Yaw from sensors
    5. Calculate delta (Roll, Pitch and Yaw)
    6. read actual Speed of Motors from sensors 
    7. Run NN 
    8. get Outputs  ( new Speed of motors ) from NN
    9. Set New Motor speeds
    10. goto 2
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