Toward intelligent machining: Hierarchical fuzzy control for the end milling process

被引:36
作者
Haber, RE [1 ]
Peres, CR
Alique, A
Ros, S
Gonzalez, C
Alique, JR
机构
[1] Univ Oriente, Dept Telecommun, Santiago De Cuba 90900, Cuba
[2] Univ Fed Santa Catarina, GRUCON, BR-88040900 Florianopolis, SC, Brazil
[3] CSIC, Inst Automat Ind, Madrid 28500, Spain
关键词
end milling process; fuzzy control; hierarchical systems; machine tool control; nonlinear process;
D O I
10.1109/87.664186
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The difficulties in implementing adaptive and other advanced control schemes in industrial machining processes have encouraged researchers to combine the utilization of one hierarchical level, a fuzzy control algorithm, and robust sensing systems, The main idea of this paper deals with self-regulating controllers (SRC's). The control signal's scaling factor (output scaling factor) is self-regulated during the control process, and it can assure the optimum gain setting for the hierarchical fuzzy controller. An important role in this strategy is performed by a robust sensing system based on current sensors, Far comparison, the CNC-PLC's own control loops, a hierarchical fuzzy controller based on look-up tables, and the hierarchical fuzzy controller with a serf-regulating output scaling factor by are studied, The performances of these controllers ate compared, The results indicate that the hierarchical fuzzy controller with a self-regulating output scaling factor yields the best performances among them, The index known as the metal removal rate is increased, and the in-process time is reduced by 50%. Thus, higher production rates are obtained. The hierarchical fuzzy controller is equipped with three basic requirements: flexibility, low cost, and compatibility with any CNC manufacturer.
引用
收藏
页码:188 / 199
页数:12
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