TY - JOUR
T1 - Interval type-2 fuzzy neural network control for X-Y-Theta motion control stage using linear ultrasonic motors
AU - Lin, Faa Jeng
AU - Chen, Syuan Yi
AU - Chou, Po Huan
AU - Shieh, Po Huang
N1 - Funding Information:
The author would like to acknowledge the financial support of the National Science Council of Taiwan, ROC, through its Grant NSC 95-2221-E-259-042-MY3.
PY - 2009/1
Y1 - 2009/1
N2 - An interval type-2 fuzzy neural network (IT2FNN) control system is proposed to control the position of an X-Y-Theta (X-Y-θ) 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-θ 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.
AB - An interval type-2 fuzzy neural network (IT2FNN) control system is proposed to control the position of an X-Y-Theta (X-Y-θ) 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-θ 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.
KW - Gradient descent method
KW - Linear ultrasonic motors
KW - Type-2 fuzzy logic system
KW - Type-2 fuzzy neural network
KW - X-Y-Theta motion control
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U2 - 10.1016/j.neucom.2008.02.013
DO - 10.1016/j.neucom.2008.02.013
M3 - Article
AN - SCOPUS:58149456900
VL - 72
SP - 1138
EP - 1151
JO - Neurocomputing
JF - Neurocomputing
SN - 0925-2312
IS - 4-6
ER -