5.19.09

Last weekend I ran a couple long SPGD experiments with and without the SLM to see if it had any noticeable effect on the performance. I ran each lasted for around 10,000 iterations, and since I can only update the SLM every 3 seconds they each took over 8 frickin hours to run. I feel like a biologist.



For the "w/ SLM" case the image was set to a focus with a sinusoidally varying intensity such that the maximum phase distortion occurs at the center of the focus at the peak sinusoidal amplitue. Maybe I'm just cynical, but its not really clear to me that the SLM has any effect. Its nice the the algorithm can sort of maximize the image cost function (J), ignoring those unexplained spikes, but its hard to distinguish any difference between the 2 cases. Control starts at k=1000.

Here's a close up of a section of the uncontrolled iterations.



The SLM obviously has an effect on the objective function, but its not much, and it doesn't look like that effect more than the noise from calculating the image objective function. What is clear though is that unless I can speed things up, using the SLM at all is totally impractical. This 3 second bullshit can't go on if I'm going to really be using it.

I'm not totally convinced the SLM is doing much to the phase. I'm pretty sure its working, but since I'm not measuring the phase directly I don't know if a single wavelength of change is much.

It's clear that something is happening. Here's a plot of the target image variance (J) and slope vector norm with the SLM active. At 300 iterations it displays a focus shape (not that easy to calculate efficiently!) where the amplitude varies sinusoidally from the max displacement to min.



The good news is that the sinusoidal pattern is reflected in both objective functions. But although the change is visible, its miniscule percentage compared to what's available with the DM. As a comparison, the maximum stroke of the DM is in the range of 10 microns. The SLM is limited to 2pi rad, about 650 nm. This wouldn't matter much if I were mapping the phase measurement back to the range of [0,2pi], such as with a SRI. But since I'm not measuring the phase directly, I'm not sure how variations like that are mapped in a Hartmann sensor.

The other problem is the ludicrously slow response time of the SLR, which I still have to limit to 1/3 Hz. Given the shit this thing has given me over the last few months, I think the best plan of action is to convince my advisor to ditch the SLM and get another DM. That will require me to exhaust all obvious ways to speed things up, but at this rate that shouldn't be hard.

6.4.09

I've spent most of this week porting my control algorithms to Simulink and the "suggestion" of my adviser. Conceptually this shouldn't be that hard since I already have a simulation using the experimental poke matrices. Reading the WFS image is trivial with the image acquisition toolbox. However implementing my custom code for calculating slopes and sending commands to the mirror requires me to use these Embedded Matlab blocks that translate m-files into C code for execution in Simulink, and that process involves a whole shit storm of issues. I found a pretty simple, slightly cheating, way of doing it that basically just involves calling my existing code as "extrinsic" functions that don't compile into C, but instead run in the Matlab workspace. This seems to work pretty well and right now I have my PI controller running beautifully (albeit slowly) in Simulink.

I've gotten the code necessary to control the SLM from Matlab as well, and its pretty clunky and generally crap, although I guess its functional enough to use. Getting it to work in Simulink as above though is, not surprisingly, a pain in the ass.

Tomorrow we meet with some Ophthalmologists to see if we can use any AO techniques on their retinal imaging machines. This has been done before by some people at Berkeley, so what they ask for might not be particularly novel, probably difficult (getting the optics setup), and from a control perspective not very interesting (the phase distortion of the eye is basically constant). Still, it doesn't hurt to talk.

At long last the SLM is installed and appears to be working. Here's the reconstructed phase with a test image:



See the face smiling at its own existence? Happily, this also indicates my phase reconstructor is working

Next comes controlling it from Matlab.

1. Cut a Hole in a Box

Finally received all the cables to install the SLM. In one final kick to the balls the connector for this new cable was too wide for the back of my PC case, so I had to pry this pointless plastic cover off the back. Why Dell shields their cases with useless crap like that I don't know.

I did some basic realignment and it looks like everything is attached correctly. Tomorrow I'll do some testing to see if the SLM's producing the phase changes its supposed to. After that, I need to figure out a way to get it working from Matlab.

In other news I've been working on the SPGD simulation with dynamic colored noise and multiple channels. To my surprise it actually works pretty well if the noise is kept to around 1% of the Nyquist frequency, but my adviser tells me this is pretty good. The idea is that by using the Strehl as the cost criteria potentially allows for the use of a photodiode instead of a full wavefront sensor. Thus, performance would probably only limited by the bandwidth of the DM controller, rather than the WFS framerate. Ideally, this would mean that sampling rates in the KHz range would be possible (and cheap).

Here are some typical results using 3 channels. More channels seem to work, but tuning the parameters is a bitch. In particular, the spikes in the cost function can be reduced by increasing the size of the perturbations, which (I think) get swamped by the disturbance sequence with higher noise variances.



Control begins at iteration 5000. This plot doesn't show the change in the cost function due to the dithering at each step to estimate the gradient. Its hard to tell from the plot, but the controlled cost function has an average value that is around 40% of the uncontrolled average. Note that these results don't look as good as those a couple days ago. In those results I forgot that I had a sinusoidal disturbance in addition to the colored noise sequence.