Hello,
I'm performing system identification of the lateral closed-loop dynamics of a quadrotor.
My model receives a setpoint and should return position and acceleration.
I've proposed a second order model of the type, see pictures, and solved it with MATLAB's greyest():
The model performs very well for the position, 97% on a cross-validation dataset, but the performance is very low for acceleration 43%.
Note the acceleration dataset comes out from an accelerometer so it's noisy, I've already tried low pass filtering the noise to improve performance with no positive results.
Any ideas on how to improve this?
Thanks!
Dear Ben Romarowski,
I suggest you to see links and attached files on topic.
https://www.hindawi.com/journals/aaa/2014/320526/
https://core.ac.uk/download/pdf/47181924.pdf
https://thesai.org/Downloads/Volume9No4/Paper_47-Modeling_of_Quadrotor_Roll_Loop.pdf
https://digitalcommons.lsu.edu/cgi/viewcontent.cgi?article=7132&context=gradschool_disstheses
https://www.beneluxmeeting.nl/2018/uploads/papers/boa.pdf
Best regards
Dear Ben, just a naive comment. I think that obtaining a better performance on position is completely natural, given that acceleration is integrated twice, and therefore the noise is smoothed by the two integrations. If I understand well, this might suggest that the identification is good, and the low performance is only due to the noisy measure.
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