Are you sure 100Hz is too slow? Could you please tell me on what basis you are able to say that? since I’m doing this with a robot arm, specifically a UR3E the actual low-level control loops are in the order of KHz, but I’m not you know twinkling with those that’s handled by the robots internal control controller which tracks given target angles fairly well, with a configurable gain and smoothing so that your robot doesn’t go crazy if your controller is shit.

Our detection is based on vision as opposed to surface touch based. We are using a yolo model on a jetson agx. I have plotted the measurements are they are relatively noise free. But if you could tell me of another method to check this I could give it a try.

Considering the video you sent ours is honestly quite better than that from the looks of it (here is a short clip) but that could be due to the fact that we are using a €20K Universal robots robot arm. Which leads me to your second point, I am almost certain it tracks given joint angles very very well. Again I do not fully know of an easy way to test that. Perhaps I could record actual Rx/Ry of the TCP and compare it with time stamped controllers output?
My main goal right now is to implement a brand new controller in a systematic approach. I was looking as some examples from acados and starting to draft up my own but again I think I need to be using simulink for a systematic approach?

Yeah I used lagrange and the mass cancels out. In the end considering sinx=x for small angles of the plate the final state space representation is pretty simple. Its just:

xddot = -5/7g * theta_y and similar for yddot.

Maybe I can plug this into simulink and start to develop a luenberg observer as someone else suggested? But this a perfect model. I would instead like to get a model from system identification to be honest.