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This thread is privately moderated by Jack Crossfire, who may elect to delete unwanted replies.
Jun 08, 2007, 02:58 PM
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Aliasing nihilism

So decided to go back to gyro elimination without Kalman filtering. Just averaged raw gyro data and fed it to a simple PID loop with P=0.1, I=0.1, D=0.1. On the test stand, it ran exactly like a rate gyro. No oscillation, searching, wobbling, crash, and very stable.

Then with the blades reattached, the oscillation returned. So why does she oscillate with blades attached and work perfectly without blades? It's pointing to aliasing of the fuselage vibration by downsampling of the gyro input.

The fuselage vibration is downsampled when the gyros sense it and again when the software averages. Both times, oscillations above the nyquist limit end up mirrored at a lower frequency in the output.

So we have to eliminate frequencies above the nyquist limit before averaging the gyro data and make 2 assumptions: Assume the gyros eliminate aliasing in their sensing. Assume all sampling before the lowpass filter is way above the fastest oscillation.

So the IDG300 has a cutoff filter at 140Hz and the ARM reads the IDG300's at 172Hz, so we shouldn't have any aliasing on the gyro side. Then the ARM averages to 30hz. Any oscillation between 15Hz and 140Hz gets downshifted.

A lowpass filter is a scary thing. Where should it cut off? Keep plugging in values until graphs of the averaged result stop showing aliasing? It's been 7 years since our last FIR filter implementation. How did we do it?
Last edited by Jack Crossfire; Jun 08, 2007 at 03:49 PM.
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