DocumentCode :
944631
Title :
Robust Adaptive Backstepping Motion Control of Linear Ultrasonic Motors Using Fuzzy Neural Network
Author :
Lin, Faa-Jeng ; Shieh, Po-Huang ; Chou, Po-Huan
Author_Institution :
Dept. of Electr. Eng., Nat. Central Univ., Chungli
Volume :
16
Issue :
3
fYear :
2008
fDate :
6/1/2008 12:00:00 AM
Firstpage :
676
Lastpage :
692
Abstract :
A robust adaptive fuzzy neural network (RAFNN) backstepping control system is proposed to control the position of an X-Y-Theta motion control stage using linear ultrasonic motors (LUSMs) to track various contours in this study. First, an X-Y-Theta motion control stage is introduced. Then, the single-axis dynamics of LUSM mechanism with the introduction of a lumped uncertainty, which includes cross-coupled interference and friction force, is derived. Moreover, a conventional backstepping approach is proposed to compensate the uncertainties occurred in the motion control system. Furthermore, to improve the control performance in the tracking of the reference contours, an RAFNN backstepping control system is proposed to remove the chattering phenomena caused by the sign function in the backstepping control law. In the proposed RAFNN backstepping control system, a Sugeno-type adaptive fuzzy neural network (SAFNN) is employed to estimate the lumped uncertainty directly and a compensator is utilized to confront the reconstructed error of the SAFNN. In addition, the motions at the X axis, Y axis, and Theta axis are controlled separately. The experimental results show that the contour tracking performance is significantly improved and the robustness to parameter variations, external disturbances, cross-coupled interference, and friction force can be obtained, as well using the proposed RAFNN backstepping control system.
Keywords :
adaptive control; fuzzy control; linear motors; machine control; motion control; neurocontrollers; robust control; ultrasonic motors; Sugeno-type adaptive fuzzy neural network; cross-coupled interference; friction force; fuzzy neural network; linear ultrasonic motors; position control; robust adaptive backstepping motion control; single-axis dynamics; $X$-$Y$- $Theta$ motion control; Backstepping control; Sugeno-type adaptive fuzzy neural network; linear ultrasonic motors;
fLanguage :
English
Journal_Title :
Fuzzy Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6706
Type :
jour
DOI :
10.1109/TFUZZ.2007.903333
Filename :
4358824
Link To Document :
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