Artificial Neural Network Compensation Technique for A PD Controlled Inverted Pendulum

Abstract

This study presents the design of the decoupled neural network reference compensation technique (DNNRCT). The technique is applied to the control of a two degrees-of-freedom inverted pendulum mounted on an x-y table. Neural networks are used as auxiliary controllers for both the X axis and Y axis of the PD controlled inverted pendulum. The DRCT method is used to compensate for uncertainties at the trajectory level and used to control both the angle of a pendulum and the position of a cart simultaneously.