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Z. Jamaludin, H. Van Brussel and J. Swevers, “Friction Compensation of an XY Feed Table Using Friction-Mo del-Based Feedforward and an Inverse-Model-Based Dis turbance Observer,” IEEE Transactions on Industrial Electronics, Vol. 56, No. 10, 2009, pp. 3848-3853. doi:10.1109/TIE.2009.2017560

has been cited by the following article:

• TITLE: Robust Adaptive Neural Network Control for XY Table

  AUTHORS: Nguyen Hoang Giap, Jin-Ho Shin, Won-Ho Kim

  KEYWORDS: Robust Adaptive Neural Network; Motion Control; XY Table; DSP

  JOURNAL NAME: Intelligent Control and Automation, Vol.4 No.3, August 7, 2013

  ABSTRACT: This paper proposed a robust adaptive neural network control for an XY table. The XY table composes of two AC servo drives controlled independently. The neural network with radial basis function is employed for velocity and position tracking control of AC servo drives to improve the system’s dynamic performance and precision. A robust adaptive term is applied to overcome the external disturbances. The stability and the convergence of the system are proved by Lyapunov theory. The proposed controller is implemented in a DSP-based motion board. The validity and robustness of the controller are verified through experimental results.