Dynamic modeling and parameter identification for a gantry-type automated fiber placement machine

Abstract

Dynamic models play a critical role in the design of model-based controllers, and therefore have a significant effect on the dynamic characteristics of motion equipment. We mainly focus on the dynamic modeling and parameter identification for a gantry-type automated fiber placement (AFP) machine in this paper. First, a dynamic modeling process combining prismatic axes and revolute axes is conducted by the Newton-Euler method, in which the effects of friction and hydraulic balance system are also considered. Then, as the convenience for parameter identification and the application in linearity control, the methods of dynamic model linearization and determination of minimum inertial parameters based on the multi-body system (MBS) theory are proposed, and a dynamic model in the form of linearized minimum inertial parameters is consequently established.To identify the parameters in the model, key issues regarding excitation trajectory, filtering, and identification algorithm are discussed in detail. Finally, corresponding experiments are performed on the AFP machine, and experimental results show that there is a good agreement between the prediction of the model and the measurement in actuality. Data analysis shows that except for Zaxis, the relative error rates of the others are not greater than 5%, which proves the effectiveness of the established dynamic model and the identified parameters.