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Robust Adaptive Neural Network Control for XY Table
Department of Intelligent System Engineering, Graduate School of Dong-eui University, Busan, South Korea
Department of Mechatronics Engineering, Dong-eui University, Busan, South Korea
Department of Mechatronics Engineering, Dong-eui University, Busan, South Korea
- 1 Department of Intelligent System Engineering, Graduate School of Dong-eui University, Busan, South Korea
- 2 Department of Mechatronics Engineering, Dong-eui University, Busan, South Korea
- 3 Department of Mechatronics Engineering, Dong-eui University, Busan, South Korea
Intelligent Control and Automation·Volume 04 (2013)·Pages 293–300·Published 7 August 2013·DOI10.4236/ica.2013.43034
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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.
KeywordsRobust Adaptive Neural NetworkMotion ControlXY TableDSP
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