Is there a mathematical solution for preventing fly-aways?

My understanding is that the following is what causes them:

- Accel z goes negative due to ship vibration versus an actual drop in altitude
- The ship corrects by adding power
- The added power causes a larger vibration-induced negative z
- The ship corrects the pseudo altitude drop by adding more power
- A fly away occurs

My understanding of mathematical solutions are:

- A filtered or weighted z only diminishes (does not solve) the effect.

Has anyone tried a "significant z", z / s, where s is the moving average of the variation of z?
- when the IMU isn't vibrating, s is low so the magnitude of z / s is high
   ... z is significant
   ... z can be trusted for use in altitude control
- when the IMU is vibrating,   s is high so the magnitude of z / s is low
   ... z / s has less effect
   ... and will not caused a flyaway

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@Chris Hawley,

I can provide you with math-physical solution to the fly-away syndrome.

It's easy to understand, accelerometer, barometer, gyroscope and other sensors were designed and built not to study airborne vibrations of the airframe itself but to study and control the drone to fly safely.

Pixhawk, server-side sensor handlers are made of tens, hundreds of code loops, so we have tens of software clocks, timing clocks and sensor clocks.

If accelerometer is clocked 1KHz and airframe starts to resonate at 1KHz so depending on the phase shift between clocks, the value you can get is max negative value, 0 value or max positive value (within range).

Since phase shift between clocks is not controlled so you get random values from sensors like accelerometer, barometer, gyroscope.

Wind tunnel Lite for small personal drones is exactly the right approach to start with to study Drone Fly-away Syndrome at OpenFabLab or via Peer to Drone Crash Investigators.

Commercial drone model types can be designed and built to no show Drone Fly-away Syndrome since sensor hardware can be preselected and sensor clocks fine tuned via FFT analysis, not to match airframe resonant frequencies.

Personally assembled drone can be affected by Drone Fly-away Syndrome in every case since you don't get prior test knowledge to make improvements.

Testing personal drone on vibrating table indoor,  phase shifting airframe resonant frequencies to match ones of sensors and software loops (sensor handlers) is what I can offer you at OpenFabLab.

email me if you are interested to study and test your drone.


If the frame reaches "resonant frequency" it will BREAK !!! What does resonant frequency of mechanical vibration have to do with the phase of a accel signal in relation to the mechanical of the frame ??? How are you linking the two ? If the frame is in a resonant frequency how can it also be in phase with the accel sensors ?  It has to be a controlled closed loop added vibration.. which drone is doing that ? maybe the Darius drones...

@Tony K,

you are not correct,

resonant frequencies are present with Diesel cars if motor idles

and chassis vibrates at resonant frequency, motor vibrates at resonant frequency and nothing breaks.

Musical instruments like violin, gran piano, guitar are made of resonant chamber, that doesn't break if you play them.

You can test Helmholz resonance frequency making beer bottle whistle.

So  drone airframe generally don't break at resonance frequency since energy consumed and transferred into vibrations is limited and self-damping mechanism works making vibration frequency to fluctuate.

But at resonant frequency amplitude of vibrations is increased greatly

to invoke Fly-away Syndrome, making phase shifted sensors to output

data to handlers at fixed clock frequency FFT correlated to resonant frequency of the drone's airframe.

For sine wave open Wikipedia

For phase shift open Wikipedia

For resonance, resonant frequency open Wikipedia

For Helmholz Resonator open Wikipedia (for Himalayan vase)

For Fast Fourier Transform FFT open Wikipedia


How are you linking the two ? If the frame is in a resonant frequency how can it also be in phase with the accel sensors ?


I said:

Since phase shift between clocks is not controlled so you get random values from sensors like accelerometer, barometer, gyroscope.

Reading data from sensor clocked at 100Hz, modulated by sine wave vibrations (at resonant frequency) can result in any value from a range

(-amplitude , + amplitude) if sensor's data handler is clocked at 100Hz

and sensor's clock and handler's clock are phase shifted.

(open Sine wave link above)

Vibrations outside of resonant frequency range (values) get damped by airframe construction, installed weights ( motors, battery) and airframe layout, mounting scheme, since amplitude of vibrations is low.

Only at resonant frequencies amplitude of vibrations can result in

Fly-away Syndrome, if supported by matching between resonant frequency and frequency of sensor's data handler.

Sensor can be clocked at higher frequency (vide GPS)

but what matters is frequency at which sensor's data are read by handler.

Ok, I don't claim the above to work as 100% explanation to Drone Fly away Syndrome but the above has been studied and verified at Vibrating Tablet for resonant frequencies of a drone, drone's airframe at OpenFabLab.

Hey Darius,

What drones do you fly?  Those of us who follow your posts are assuming that you fly an MR, because you focus on Drone FlyAway Syndrome so much.  FlyAways are less common in ArduPlane.  Do you fly a quad, a hex or an X8?  

Some photos of one of your recent builds pointing out the modifications that you've implemented to reduce FlyAways  would be appreciated!


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