I used to be like OP. (have a similar background and have similar interests in tech for the planet)
Then I realised couple of things, an humbling experience:
1) given any position on earth, you can compute exactly what's the optimal inclination at any given point in time for a PV to maximize the energy production. Sure, there are reflection and secondary irradiation conditions (eg.: there is a lake close to it), but again, assuming the environment is static, it's way faster to just compute it statically rather than dynamically. Also, in most scenarios Beam irradiance from diffusion (the beam hitting the object) is order of magnitude higher than from reflective one (the same beam bouncing on a 3rd object first).
2) In mechanics movable part are the things to avoid. They have lower MTBF (mean time before failure) and as such they introduce complexity and increase cost
3) Economics is a key component of engineering. There is a cost to everything, the computational power, the energy needed by the servo, etc, etc. Given 1 and 2, a dynamic solution simply has a lower ROI than a static one.
I really appreciate the OP exploration here: there is a good overview of basic control theory and a good foundation of ML (although don't be deceived, this is a very simple modelling task that OP is overkilling with a way more complex model). That said, for everyone reading, this is not something you want to do in a real world situation.