Parameters Identification of a Five-Axis Machine Tool by Haar Wavelet

摘要

Physical parameters in the dynamic model of a machine tool have to be concerned in order to design and develop model-based control algorithm. This work presents the parameter identification for a 5-axis machine tool. The system dynamics is strongly nonlinear, but can be linearly parameterized with 12 unknown parameters. The parameter identification is based on the representation of all of the known time functions in the dynamic equations with orthogonal Haar wavelet functions. Then, the least square method is utilized to obtain the unknown parameters. The experimental results show that the predicted response generated by the identified parameters matches with the measured actual response. The relative RMS prediction errors are all less than 12%, verifying the effectiveness of the identified parameters.