Nonlinear position estimators based on artificial neural networks for low costs manufacturing systems

• Autorzy: Dogruer C. , Kilic E. , Dolen M. , Koku B.
• Języki publikacji: EN

Abstrakty

EN

The accurate contral of CNC machine axis requires relatively expensive direct measurement sensors. In this paper, artificial neural network based position error estimators are comparatively evaluated as a part of a low-cost (but high performance) manufacturing system. Such schemes are very effective when the system is rot subjected to external loads as well as widely changing operating conditions such as ambient temperature.

Słowa kluczowe

EN

neural networks; esimators

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2007
• Tom: Vol. 1, No. 2
• Strony: 40--44
• Opis fizyczny: Bibliogr. 9 poz., rys.

Twórcy

autor

Dogruer C.

autor

Kilic E.

autor

Dolen M.

autor

Koku B.

• Middle East Technical University, Department of Mechanical Engineering, Ankara, 06531, Turkey

Bibliografia

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• [7] X. Li, "Real-time prediction of workpiece errors for a CNC turning centre. Part 2. Modeling and estimation of thermally induced errors", Int. J. Adv. Manuf. Technol., 2001, vol. 17, pp. 649-653.
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