Adaptive Fuzzy Neural Network Control System in Cylindrical Grinding Process

Abstract:

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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 and 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

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Price:

$35.00

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