Application of fuzzy sliding mode control method based on cyber-physics fusion system in mechanical resonance suppression

Abstract

Modern high-end digital manufacturing has continuously improved the performance requirements for servo drive systems. High-performance servo drive systems should have excellent dynamic performance and steady-state performance. At present, an AC permanent magnet servo drive system using a permanent magnet synchronous motor as the drive motor has become the mainstream of contemporary servo drive systems. Servo system (servo mechanism), also known as servo systems, generally contains feedback control links, mainly used to accurately follow or reproduce a certain process. The servo system is mainly composed of a controller, a power drive device, a feedback device, a transmission device, a motor, and a load. In a servo system, the existence of mechanical resonance will cause serious damage to the transmission mechanism of the system and will reduce the reliability and accuracy of the system. When the performance of the system deteriorates severely, it will lead to system instability or even safety accidents. This article aims to study the use of fuzzy sliding mode control methods to control the generation of mechanical resonance, to further eliminate the phenomenon of mechanical resonance in the servo system. This paper puts forward the methods to eliminate chattering generated by sliding mode control, mainly including filtering method, eliminating uncertainty, intelligent algorithm optimization, reducing switching gain, and fan shape. The experimental results in this paper show that when the angular speed feedback of the motor is adopted, the maximum value of the speed difference is close to 3rad/s. It can be considered that there is resonance in the system, and the load resonance is the main factor. When the angular velocity feedback at the load end is used, the maximum value of the speed difference is about 0.05rad/s, and it can be considered that the resonance has been successfully suppressed.