Interval type-2 fuzzy neural network control for X-Y-Theta motion control stage using linear ultrasonic motors

Authors:
Faa-Jeng Lin;Syuan-Yi Chen;Po-Huan Chou;Po-Huang Shieh
Affiliations:
Department of Electrical Engineering, National Central University, Chungli 320, Taiwan;Department of Electrical Engineering, National Central University, Chungli 320, Taiwan;Department of Electrical Engineering, National Dong Hwa University, Hualien 974, Taiwan;Department of Electrical Engineering, National Dong Hwa University, Hualien 974, Taiwan
Venue:
Neurocomputing
Year:
2009

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Abstract

An interval type-2 fuzzy neural network (IT2FNN) control system is proposed to control the position of an X-Y-Theta (X-Y-@q) motion control stage using linear ultrasonic motors (LUSMs) to track various contours. The IT2FNN, which combines the merits of interval type-2 fuzzy logic system (FLS) and neural network, is developed to simplify the computation and to confront the uncertainties of the X-Y-@q motion control stage. Moreover, the parameter learning of the IT2FNN based on the supervised gradient descent method is performed on line. The experimental results show that the tracking performance of the IT2FNN is significantly improved compared to type-1 FNN.