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This study is concerned with the problem of system identification for permanent magnet linear synchronous motor(PMLSM) based motion systems with disturbances such as parametric uncertainty, friction force, and force ripple. In order to identify the disturbances, a novel system identification method is proposed. The main idea of the proposed scheme is to separate and identify each element from a lumped disturbance by using even and odd characteristics of the state-dependent disturbances. The lumped disturbance is estimated by a linear disturbance observer(DOB), that includes the parametric errors, the friction force, and force ripple. To facilitate the decomposition of the lumped disturbance, the symmetric reference position trajectories are utilized, which make it useful to keep the even and odd characteristics of each element. The even and odd elements separated from the lumped disturbance by the decomposition method are represented as the force ripple multiplied by the mass error and the friction force multiplied by the viscous friction coefficient error, respectively. By comparing with experimental results based on different reference velocities and acceleration trajectories, the parametric errors are identified first, and then, nonlinear disturbances such as the force ripple and friction forces are identified by curve-fitting methods using the experimental data. The validity of the proposed scheme is illustrated by experimental tests. The effectiveness of the identified system elements is also verified by comparison with the position tracking performances of comparative studies.

System Identification Method Based on a Disturbance Observer Using Symmetric Reference Trajectories in PMLSM-Based Motion Systems