Abstract
Nonlinear frictions in feed drive axes affect the control accuracy and dynamic of the machine tools. Conventional dynamic friction models neglect the position-dependent friction, caused by manufacturing errors and misalignment as well as the environment. This paper proposes an extended LuGre friction model for estimating the dynamic and position-dependent friction effects. The conventional LuGre model is modified by a position-dependent term, which describes the nonlinear friction behavior of machine axes with long travel distance. An online data-driven identification approach is developed to fast parametrize and update the model. The suggested method is validated on a real machine tool.
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