Fuzzy Controller for Flatness Based on Neural Network Pattern-recognition

Jian-chang Liu, Zhu Wang

Abstract

A pattern-recognition method for flatness defect based on CMAC neural network is proposed, and a flatness fuzzy controller based on the pattern-recognition results is designed in this paper. Pattern-recognition and controller are designed into a single unit, in which CMAC recognizes the membership grade relative to six basic modes of common flatness defect and realizes the seeking function of the membership grade as the forepiece of the fuzzy controller for flatness directly. Through analyzing the characteristics of the flatness defect, the fuzzy set is defined reasonably, which has greatly reduced the calculation amount of fuzzy reasoning. The result of simulation shows that the pattern-recognition method of flatness offers high recognizing precision, the designed fuzzy controller for flatness can control the flatness defect to expected goal fleetly and the performance of flatness control is fine.

References

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Paper Citation


in Harvard Style

Liu J. and Wang Z. (2005). Fuzzy Controller for Flatness Based on Neural Network Pattern-recognition . In Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2005) ISBN 972-8865-36-8, pages 42-51. DOI: 10.5220/0001191600420051


in Bibtex Style

@conference{anniip05,
author={Jian-chang Liu and Zhu Wang},
title={Fuzzy Controller for Flatness Based on Neural Network Pattern-recognition},
booktitle={Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2005)},
year={2005},
pages={42-51},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001191600420051},
isbn={972-8865-36-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2005)
TI - Fuzzy Controller for Flatness Based on Neural Network Pattern-recognition
SN - 972-8865-36-8
AU - Liu J.
AU - Wang Z.
PY - 2005
SP - 42
EP - 51
DO - 10.5220/0001191600420051