Applying reinforcement learning to solve a non-stationary modeling and control problem for power generation for a dual-axis solar panel.
Complete project details at: https://www.jackogrady.me/reinforcement-learning-solar/research-summary
firmware/: holds Arduino firmware as well as interface READMEs for Arduino-Python communicationrl_agent/: holds all code for the final agent design (Softmax Actor-Critic) as well as dev agentsschemtics/: Circuit and system schematics for the project
First, install the required Python libraries which you can view in the requirements file. Simply run
pip install -r requirements.txt from this directory to install them in your interpreter.
Next, I'd recommend going to > rl_agent > README, which explains everything about
the agent and how to run it. If you're more interested in the solar panel and Arduino, head to
> firmware > README to learn about that.
An Important Note
This code repository is really meant to be consumed in tandem with the material and the link above. At that link, you can read about larger design aspects, concepts, and see experiment results (but more importantly, see how everything ties together)
The repository exists so that anyone interested in RL can see an end-to-end implementation of code, as well as the experimentation along the way to get to the code.
Copyright 2022 Jack O'Grady
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