Model Reference Adaptive Control and Fuzzy Neural Network Synchronous Motion Compensator for Gantry Robots

Chin-Sheng Chen,Nien-Tsu Hu

doi:10.3390/en15010123

Abstract

A model reference adaptive control and fuzzy neural network (FNN) synchronous motion compensator for a gantry robot is presented in this paper. This paper proposes the development and application of gantry robots with MRAC and FNN online compensators. First, we propose a model reference adaptive controller (MRAC) under the cascade control method to make the reference model close to the real model and reduce tracking errors for the single axis. Then, a fuzzy neural network compensator for the gantry robot is proposed to compensate for the synchronous errors between the dual servo motors to improve precise movement. In addition, an online parameter training method is proposed to adjust the parameters of the FNN. Finally, the experimental results show that the proposed method improves the synchronous errors of the gantry robot and demonstrates the methodology in this paper. This study also successfully integrates the hardware and successfully verifies the proposed methods.

Highlights

Gantry robots have been widely used in manufacturing industries such as highprecision motion control, precision manufacturing, circuit assembly, microelectronics, and inspection [1,2,3]
The gantry robot is composed of a manipulator on an overhead system, and two motors are installed on two parallel linear guides to drive the moving platform
Due to various factors, such as unbalanced forces on both sides, various disturbances in the driving process will cause synchronous errors between the two motors. The consequence of these synchronous errors will cause system jitter and affect the quality of the workpiece and cause the work process to stop due to overcurrent protection

Summary

Introduction

Gantry robots have been widely used in manufacturing industries such as highprecision motion control, precision manufacturing, circuit assembly, microelectronics, and inspection [1,2,3]. Typical methods (see Figure 1) to synchronize the motion in gantry robot control systems include (1) the cascade control method, and (2) the parallel control method [4,5]. Both methods use two control loops to control the motors separately. In this method, the discrete model of aGspingzl−e1ax=is pZlan1t−, wse−hiTcsh· cτaisnK+bi e1rep=re1se+bnzta−ez1d−1as ( ) Gpi z−1 is (4). We adopt the important design results of [30]

FNN Synchronous Motion Compensator

On-Line Learning Algorithm

Stability Analysis

Parallel Master–Slave Synchronous Control

Conclusions