Integrated Parameter Identification Based on a Topological Structure for Servo Resonance Suppression

Abstract

In the dual-inertia servo system, the servo resonance in which the characteristics are closely related to the mechanical parameters is usually suppressed by adding a notch filter. As a result, accurate mechanical parameter identification facilitates adjusting the notch parameters and avoiding the failed servo resonance suppression caused by the mechanical parameter mismatch. In this paper, a topological structure expanded by five improved Sliding-Mode Observers (ISMOs) is proposed to simultaneously identify the load speed, the motor inertia, the load inertia, the stiffness coefficient, and the load disturbance, where the load speed and the load disturbance are considered as intermediate variables to provide sufficient load-side information to ensure the identification accuracy of the mechanical parameters. Furthermore, according to the natural knowledge of the dual-inertia servo system, a time-varying interconnected gain with an equal derivative to the identification parameter in each ISMO is designed to promote the global convergence of the topological structure. Finally, the identified mechanical parameters are utilized to adjust the notch parameters for the servo resonance suppression. Simulation and experimental results are presented to indicate the superiority of the topological structure and the effectiveness of the servo resonance suppression.