Application of type-II fuzzy neural network to adaptive double axis motion control system

作者：Chen Xiang Jian; Li Di; Bai Yue; Xu Zhi Jun^*

来源：Optics and Precision Engineering, 2011, 19(7): 1643-1650.

DOI：10.3788/OPE.20111907.1643

• Adaptive technology
• Approximation errors
• Axis motion control
• Contour tracking
• Interval type-II fuzzy neural network
• Lyapunov stability theorem
• Optimal parameter
• Permanent Magnet Synchronous Motor
• Processing platform
• Robust compensators

An adaptive double axis motion control system to improve the accuracy of processing platforms was designed by combining the adaptive technology and the interval type-II fuzzy neural network theory. The system controlled two field oriented permanent magnet synchronous motors to locate the X-Y double axis motion rotor to track the butterfly contour. Meanwhile, a robust compensator was proposed to confront the Lumped uncertainty, including the inevitable approximation error due to the finite rules of the interval type-II fuzzy neural network, optimal parameter vectors and so on. Finally, the proposed control algorithm was implemented in a TMS320C32 digital signal processor. The experimental results indicate that the butterfly contour tracking performance of the double axis motion control system is improved significantly, and the control system based on the interval type-II fuzzy neural network is more robust than that based on the type-I fuzzy neural network for different uncertainties.

• 出版日期2011