Paper Title:
Adaptive Fuzzy Neural Network Control System in Cylindrical Grinding Process
  Abstract

An adaptive fuzzy neural network control system in cylindrical grinding process was proposed. In this system, the initial cylindrical grinding parameters were decided by the expert system based on fuzzy neural network. Multi-feed and setting overshoot optimization methods were also adopted during the grinding process, and a human machine cooperation system (composed of human and two fuzzy – neural networks) could revise the process parameters in real-time. The experiment of the cylindrical grinding was implemented. The results showed that this control system was valid, and could greatly improve the cylindrical grinding quality and machining efficiency.

  Info
Periodical
Key Engineering Materials (Volumes 426-427)
Edited by
Dunwen Zuo, Hun Guo, Guoxing Tang, Weidong Jin, Chunjie Liu and Chun Su
Pages
220-224
DOI
10.4028/www.scientific.net/KEM.426-427.220
Citation
X.M. Li, N. Ding, "Adaptive Fuzzy Neural Network Control System in Cylindrical Grinding Process", Key Engineering Materials, Vols. 426-427, pp. 220-224, 2010
Online since
January 2010
Authors
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Price
$32.00
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