关键词: PLC伺服系统, PLCopen功能块, 在线辨识, 自适应控制, 跟踪精度

Abstract: Programmable Logic Controllers (PLC) servo systems are widely utilized in precision manufacturing equipment,such as drones and industrial robots.However,variations in working conditions,including changes in inertia and nonlinear friction disturbances,significantly degrade control performance.Traditional control methods fail to provide satisfactory compensation under such conditions.To address this issue,an online identification and adaptive control method based on PLCopen was proposed.The dynamic model of the servo system was established.To mitigate the identification bias caused by nonlinear Coulomb friction,an Unbiased Recursive Least Squares (URLS) algorithm was developed for online identification of dynamic parameters.Subsequently,based on the identification results,an adaptive composite control strategy was designed.The PLC Coder tool was employed to generate PLCopen function blocks for implementation in actual systems.Experimental results indicated that the proposed parameter identification method accurately identified the dynamic parameters of the servo system,with identification accuracy superior to that of the basic least squares method.Compared to two fixed-value control methods,the proposed adaptive control method demonstrated certain advantages in speed tracking and stability.Under loaded conditions,speed tracking accuracy was improved by 34.8% and 18.9%,while stability accuracy increased by 64% and 34.7%,respectively.This study provided a valuable reference for achieving high-performance motion control in PLC servo systems.

Key words: programmable logic controllers servo system, PLCopen function blocks, online identification, adaptive control, tracking accuracy