Real Time Neural Network Control of a Twin Rotor System

Abstract

Real time intelligent control scheme that utilizes neural network to perform PID controller to control a twin rotor system is proposed. An experimental propeller setup called the twin rotor multi-input multi-output system (TRMS) is used in this study. The use of single neuron in PID control reduces system computing time that makes on-line learning and real time control feasible. The proposed control scheme can drive the TRMS to follow desired attitudes. The pitch angle and the azimuth angle in the condition of cross-coupled between vertical and horizontal axes is considered. Furthermore, the control scheme can overcome external disturbance. Simulation results show that the new approach can improve attitude tracking performance and the neural network-PID controller can work in real time.