Tracking error reduction in CNC machining by reshaping the kinematic trajectory |
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Authors: | Jianxin Guo Qiang Zhang Xiao-Shan Gao |
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Institution: | 1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China 2. College of Information and Control Engineering, China University of Petroleum (East China), Qingdao, 266580, China
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Abstract: | In this paper, a method of reducing the tracking error in CNC machining is proposed. The structured neural network is used to approximate the discontinuous friction in CNC machining, which has jump points and uncertainties. With the estimated nonlinear friction function, the reshaped trajectory can be computed from the desired one by solving a second order ODE such that when the reshaped trajectory is fed into the CNC controller, the output is the desired trajectory and the tracking error is eliminated in certain sense. The proposed reshape method is also shown to be robust with respect to certain parameters of the dynamic system. |
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Keywords: | CNC controller robustness structured neural network tracking error |
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