The annoying thing is that it occurs very suddenly, and as a result the modal sequences shoot up, almost like step response. Actually, I'm not sure which one is driving the other, but since no one's touching the experiment, I assume its the control saturation.
Some things to investigate:
1. A bad plant model. It could be that the poke matrix just isn't accurate enough for some modes, and as a result the modal commands from the LTI controller are too coupled or otherwise garbage.
2. Bad sensor data. I doubt this is the case since I've gotten the WFS image very clean, with small realignments and re-referencing every day to keep things tidy.
3. Shitty predictor. Relative prediction error's are sometimes north of 50%
4. Bad internal model. None of the nonlinear effects (rounding or saturation) are included in the controller's internal model. So when saturation does happen the predictor doesn't get an accurate estimate of the current disturbance. Obv. this would only make things worse when saturation was already happening.
5. Bad PI Gain/pole. Possible, but since the integrator is included in the ID I'm not sure the LTI controller would jsut send out higher values if I reduced the PI gain.
6. Unexplainable. The most likely.
I'm gong to see if I can reproduce the problem in simulation if playing around with the integrator gain doesn't solve things. Otherwise, I might also look at writing the code to actually calculate the optimal LTI filter instead of pulling it from the Kalman filter. Basically this involves an LQR problem, with the advantage that you can directly penalize the "size" of the predictor to try to prevent large control values.
Also, it's pretty funny looking at the keywords that send people to this blog, I guess people looking for implementations of different AO algorithms. So if you're out there: no I don't have a simulink SPGD implementation, sorry. Maybe one day.
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