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Dimensional Accuracy Enhancement in CNC Batch Grinding through Fractional Order Iterative Learning Compensation
Author(s) -
Chen Tiantian,
Tian Xincheng,
Li Yan
Publication year - 2014
Publication title -
advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
ISSN - 1687-8132
DOI - 10.1155/2014/260420
Subject(s) - grinding , compensation (psychology) , numerical control , process (computing) , iterative learning control , computer science , control theory (sociology) , machine tool , comparator , control engineering , machining , engineering , control (management) , mechanical engineering , artificial intelligence , psychology , psychoanalysis , operating system , electrical engineering , voltage
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.

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