Stabilization of double inverted pendulum with self-tuning neuro-PID

Abstract

A self-tuning neuro-PID control architecture is proposed and applied to the stabilization of double inverted pendulum. The gain parameters of the PID controller are tuned using a neural network. The effectiveness of the proposed method is shown through simulation and experiment.