Dimensional accuracy enhancement in CNC batch grinding through fractional order iterative learning compensation

Abstract

This paper presents a systematic method to compensate for dimensional errors of workpieces machined in computer numerical control (CNC) batch grinding process. The dimensional error precompensation scheme includes a fractional order compensator, automatic dimensional measuring device, and a comparator. A practical fractional order differential plus low-pass iterative learning approach is used to update the compensation for the next workpiece. An incremental order updating law is proposed for the fractional system order identification, which plays a fundamental role to optimize the performance of grinding process. Then the error compensated numerical control (NC) program is fed to the machine tool for subsequent grinding. Several illustrated results show the effectiveness of the above strategy. © 2014 Tiantian Chen et al.