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

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6 Author(s)
Haber, R.E. ; Dept. of Telecomm., Univ. de Oriente, Cuba ; Peres, C.R. ; Alique, A. ; Ros, S.
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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 (SRCs). 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. For comparison, the CNC-PLC's own control loops, a hierarchical fuzzy controller based on look-up tables, and the hierarchical fuzzy controller with a self-regulating output scaling factor GC are studied. The performances of these controllers are 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

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Control Systems Technology, IEEE Transactions on  (Volume:6 ,  Issue: 2 )