So the neural network fans swear by neural networks and the PID fans swear by PID loops. The problem with neural networks is to take advantage of the neural network features, U need a simulator to teach them. They run an evolutionary algorithm simulating a mission over and over again. The simulator doesn't reflect the real vehicle, so they have 2 B further tweeked by hand.

With a very complicated nest of PID loops U can achieve the same result as a neural network, but in a more human readable form. Maybe tanh can be used instead of CLAMP to achieve some non linearity. Maybe Vicacopter's flight control can B written as a neural network of PID nodes.

Another alternative is using differential equations of many terms to combine some of the 3 term PID loops. PID loops could B combined in a single differential equation like c1*(Position Error Integral) + c2 *(Position Error) + c3 * (Velocity Error Integral) + c4 * (Velocity Error) + c5 * (Acceleration) = Feedback. Some inputs come from directly the INS and some come from a PID loop for target velocity.

After a 48 hour break, strong winds have returned to Rain Ramon. Adding the position error integral to the feedback for velocity error seemed to improve her resistance to wind. She entered a pitch oscillation which drifted downwind instead of a complete loss of control.

Also, the derivatives are physical data straight from the sensors, so they need 2 B subtracted from the feedback result instead of added like they were. That got us exponential oscillation instead of loss of control like before.

Next, couldn't reproduce the control losses when facing south and one PID configuration file uploaded from a great distance came out corrupted.

Finally, after a hard dead battery landing the Micromag3 failed again. Power cycling it didn't work. It only worked after returning to dumpy apartment and rebooting it. Seems 2 need a long time to rest. Don't think writing it in Java would improve matters.

Some of the technical esoterica is a bit outside my ken, but I have to tell you: Your blog entries rule! A GPS-guided heli sounds just too cool for the room.

Hi,
I think the idea to use neuronal networks for replacing a PID loop is great. Actually I am wondering what you were thinking about when talking about PID loops 10 years ago.

Today I am thinking about a FPV Racing Mini Quads.

I think the training of a neuronal network could be done inflight. At the same time a traditional PID-Loop-Controller needs to recover the copter from crashing if the neuronal network isn't able to compensate a given error to a certain amount in a certain time.