Self-tuning control of a two-link flexible manipulator using neural networks

Abstract

In this paper, a self-tuning control of a two-link flexible manipulator using neural networks is presented. The neural networks learn the gains of PI controllers for the flexible manipulator. Numerical results show that this presented neural network control system can suppress the vibration of the flexible manipulator and track the desired joint angles. Simulation results show that the self-tuning control system using neural network can be used effectively for the position control of the two-link flexible manipulator.