Neural-Network Based Learning Control of Flexible Mechanism With Application to a Single-Link Flexible Arm

Abstract

This paper shows the effectiveness of a neural-network controller for controlling a flexible mechanism such as a flexible robot arm. An adaptive-type direct neural controller is formulated using state-space representation of the dynamics of the target system. The characteristics of the controller are experimentally investigated by using it to control the tip angular position of a single-link flexible arm.