Reinforcement learning based satellite control

This invention describes a method for keeping a satellite stable in its orbit. It uses a smart computer program, known as a reinforcement learning model, to learn how to adjust the satellite's orientation. The program takes in data about the satellite's current position and movement, then predicts and executes actions, learning from the outcomes to keep the satellite steady. The claims specifically narrow this to a system that uses two distinct learning agents, an "omega agent" and a "Euler agent," to manage different aspects of the satellite's stability.