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Proceedings Paper

Control of ultrahigh-precision magnetic leadscrew using recurrent neural networks
Author(s): Timothy N. Chang; Tony Wong; Danni Bhaskar; Zhiming Ji; Michael Shimanovich; Reggie Caudill
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Paper Abstract

In this work, the problem of vibration control for a contactless magnetic leadscrew system is considered. A contactless drive system is a magnetic nut/leadscrew and air bearing assembly that operates on the principle of magnetic/aerodynamic suspension to position a load with high accuracy. However, the dynamics of such system is lightly damped, load dependent, and generally difficult to stabilize by conventional linear controllers. Therefore, the technique of recurrent neural network is applied to separate the oscillatory signals so that passband shaping can be carried out to regulate plant dynamics and to reject disturbances. This controller possesses a modular structure and is easy to implement. Experimental results also confirm the vibration suppression capabilities of this controller.

Paper Details

Date Published: 17 December 1998
PDF: 12 pages
Proc. SPIE 3518, Sensors and Controls for Intelligent Machining, Agile Manufacturing, and Mechatronics, (17 December 1998); doi: 10.1117/12.332796
Show Author Affiliations
Timothy N. Chang, New Jersey Institute of Technology (United States)
Tony Wong, New Jersey Institute of Technology (United States)
Danni Bhaskar, New Jersey Institute of Technology (United States)
Zhiming Ji, New Jersey Institute of Technology (United States)
Michael Shimanovich, New Jersey Institute of Technology (United States)
Reggie Caudill, New Jersey Institute of Technology (United States)


Published in SPIE Proceedings Vol. 3518:
Sensors and Controls for Intelligent Machining, Agile Manufacturing, and Mechatronics
Patrick F. Muir; Patrick F. Muir; Peter E. Orban, Editor(s)

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