Suntan or just a bit grubby?

I coded the trend-line offsets for the accelerometer last night and have just take Phoebe out into the back garden for a quick sanity check test flight.  There was no wind, and very little drift, so the results are a bit inconclusive for the moment (other than no harm was done), but it’s probably worth my while rerunning yesterday’s trend-line tests to get the best values I can.

At the same time, Dave pointed me in the direction of gyro temperature sensitivity too.  I’m less concerned about this since the flights are currently short, the gyro is calibrated per flight, and the gyro is only used short term for rapid detection of changes in tilt – longer term, the accelerometer Euler angles take over via the complementary filter.  Still, probably worth investigating just in case, if only for longer flight drift.

Finally, Jeremy requested some flight sensor data – I’ve attached the .csv file (Excel can turn this into a spreadsheet) corresponding to one of this morning’s flights.  Just leave a comment if you want me to churn out some graphs!

10s flight stats

2 thoughts on “Suntan or just a bit grubby?

  1. Thanks for the stats. I did a plot of the c_pitch and c_roll values which I assumed were the pitch and roll angles (as calculated by the complementary filter) relative to the earth’s surface, correct? Graph can be found here https://drive.google.com/file/d/0B4fjVY-sotl9em44ZDFSMkJqd0k/edit?usp=sharing
    It’s interesting to see the dynamics of the copter and to think about what can be inferred from the data. e.g. The maximum gradient of the curves are likely due to the copter’s mass and the way it’s distributed vs. motor torque curve (coupled with current PIDs). It does look like these curves could also help to fine-tune PIDs. Imagine adjusting PIDs on the fly based of the derivative of these curves. Could this lead to a more stable platform? Maybe. Just a thought.

    • Hi Jeremy,

      Yes, your interpretation of c_pitch and c_roll is correct. Sadly google is being awkward, so I can’t see your plots – I’ll have another go later.

      Dynamic PID tuning! Interesting – I’ll add it to my list – but for the moment I need to focus on sensor accuracy, resolution, and complementary filter angles – without these being as near to perfect as possible, the PIDs are doomed (GIGO). Have a look at the plots of sensor output from a stable, horizontal platform vs. temperature. It’s more than enough to make Phoebe think she’s hovering horizontally when in fact she’s drifting. So that’s my critical Fish to Fry at the mo.

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