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Topic: Quadcopter stabilization algorithm (Read 20 times) previous topic - next topic

jabbado


The way I'd approach this is similar to the algorithm used for NTP

Is that Marzullo's algorithm you're talking about?

jabbado


I fly paragliders for a living so I'm familiar with thermals.

That's not a job. It's getting paid to have fun :)
I was looking at the KK boards since you mentioned them several days ago. But I can't find much info on firmware etc.

sbright33

#37
Dec 05, 2012, 03:00 pm Last Edit: Dec 05, 2012, 03:03 pm by sbright33 Reason: 1
Be careful there is more than one version of the hardware.  
Within each, there is more than one version of the firmware.  
Look here under the Files tab:
http://www.hobbyking.com/hobbyking/store/__19534__HobbyKing_Multi_Rotor_Control_Board_V2_1_Atmega168PA_.html
Or Google kk board firmware v2.1?
I cannot see a reason to change the firmware that comes loaded when you buy it.  But you can look at the code to learn how it works.  Unless you want to download X configuration.
If you fall... I'll be there for you!
-Floor

Skype Brighteyes3333
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sbright33

I think Marzullos algorithm is overkill for our needs.  I'm not even sure how it is relevant.  But you do raise an interesting question.  It's not that the Ameter data is better than barometer.  It has more precision, and less delay.  That's the important part.  But it also has more noise.  How to use both together?
If you fall... I'll be there for you!
-Floor

Skype Brighteyes3333
(262) 696-9619

PeterH



The way I'd approach this is similar to the algorithm used for NTP

Is that Marzullo's algorithm you're talking about?


Not really.

A lot of NTP is about determining propagation delays to find the consensus time, but the part that seems most relevant here is the algorithm used to steer the local clock towards the consensus time. Rather than simply adjust the local clock to correct for any discrepancies, the algorithm aims to control the local clock by skew adjustments so that the discrepancies tend to zero. That seems analogous to the current problem of detecting and correcting long-term errors in the integrated speed/position calculations by comparing them against the low resolution, but believed accurate, barometric height measurements.


I need to make some improvements to reduce oscillating and drifting.


Not to labour the point, but this is precisely the purpose of the D and I terms in PID. Your reluctance to use a conventional PID algorithm still puzzles me; it strikes me as the simplest and most appropriate solution to this problem.
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