An inertia wheel pendulum control method based on actor-critic learning algorithm

Abstract

Based on the state-space representation of inertia wheel pendulum, Euler method is used to update the state of inertia wheel pendulum system. The effect of actor-critic algorithm on inertia wheel pendulum system control is studied with different sample time and different proportion of angle in reward. The results show that the training effect is better with smaller sample time. Because the main goal of inertia wheel pendulum control is to control the angle of the pendulum, more weight should be given to the angle in reward to make the training to be stable more easily.