Online Identification Method for Mechanical Parameters of Dual-Inertia Servo System

Rotary table servo systems are widely used in industrial manufacturing. In order to satisfy the demands of low-speed and high-torque applications, rotary table servo systems are typically applied with a reduction gear and gearbox, causing transmission system limit loop oscillation and reducing the system’s transmission accuracy. Accordingly, the single-axis servo rotary table is taken as the object of study, with the objective of enhancing the positioning precision of the load side. The identification of the mechanical parameters of the dual-inertia servo system is thus undertaken. A simplified mathematical model of the dual-inertia system is constructed, the principle of mechanical parameter identification of the dual-inertia system is elucidated, an online identification algorithm based on the forgetting factor recursive least square (FFRLS) is investigated, and factors affecting the identification accuracy are analyzed. The efficacy of the recognition algorithm is validated through simulations and experimentation. The experiments on the DSP 28,335 platform demonstrate that the dual-inertia system mechanical parameter recognition algorithm is capable of identifying rotor inertia, load inertia, and shaft stiffness online simultaneously. The recognition error is less than 10%, the recognition accuracy is high, and the algorithm exhibits a certain degree of robustness.