Parameter Optimization of Servo Drivers and Controller for CNC Machine Tools Based on Grey Relational Approach

Jenn Yih Chen; Wei Ting Lin

doi:10.4028/www.scientific.net/AMM.418.225

Paper Titles

Effect of Rotation Speeds on Friction Coefficients of PPS Race-PTFE Retainer Hybrid Polymer Thrust Bearings under Dry Contact
p.205

Size Effect of the Single Crystal Copper Based on D-P Yield Function
p.209

A Study on the Introducing Plan and Process of TPM into Taiwan Traditional Industry
p.213

Electronic Cam Trajectory Generation Algorithm Based on Global Optimal Control Points of Non-Uniform B-Spline
p.219

Parameter Optimization of Servo Drivers and Controller for CNC Machine Tools Based on Grey Relational Approach
p.225

Networked Connection of NC Machine Tools Based on MTConnect
p.229

A New Resolution about Calculating Degree of Freedom Planar Mechanism with Higher Pairs
p.234

The Study of CIGS Absorption Layer Grown by Two-Step Growth Method for Thin-Film Solar Cell
p.238

Dynamic and Analysis of a Marine Stabilization Table
p.242

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 418Parameter Optimization of Servo Drivers and...

Parameter Optimization of Servo Drivers and Controller for CNC Machine Tools Based on Grey Relational Approach

Abstract:

This paper aims at finding the optimal parameters of the servo drivers and controller for a machine tool in order to improve machining accuracy and reduce machining time. Firstly, the backlash and pitch error of a transmission device were compensated by means of the controller. The control factors of the drivers include the ratio of load inertia moment to servo motor, speed loop gain, and integral time constant of the speed loop. The control factors of the controller are the acceleration/deceleration constant of feed rate and position loop gain. Each factor was classified into three levels and each experiment was repeated three times. The experimental data were converted into the signal-to-noise (SN) ratio to obtain the response tables of the SN ratio. Finally, the grey relational method was applied to find the optimal parameters. We compared the difference of the experimental results by employing the optimal parameters and default values of the drivers and controller of the CNC machine tool. Experimental results show that machining accuracy and machining time can be improved. Therefore, the results demonstrate the effectiveness of the proposed scheme.