Adaptive Positioning Control of Servomotor Based on Model Identification

• Published in: IEEE transactions on power electronics 2022-05, Vol.37 (5), p.5272-5283
• Main Authors: Liu, Fang, Peng, Hui, Zhang, Dingyun, Huang, Xinjie, Tong, Li, Wu, Rui, Peng, Xiaoyan
• Format: Article
• Language: English
• Subjects: Acceleration; Adaptation models; Adaptive control; Adaptive positioning control; Adaptive systems; Batteries; Control methods; Controllers; Cutting equipment; Cutting speed; Deceleration; Electrode materials; Electrodes; High speed; Mathematical models; model identification; multimotor speed planning; Parameters; periodic positioning control; Planning; Positioning devices (machinery); Programmable logic controllers; Servocontrol; servomotor; Servomotors; Synchronous motors
• ISSN: 0885-8993; 1941-0107
• DOI: 10.1109/TPEL.2021.3134094

The new energy vehicle industry needs a large number of vehicle power batteries, and its production depends on high-speed and high-precision battery pole-piece cutting equipment, which is mainly composed of the electrode material roll uncoiling unit, buffering unit, main drive unit, and cutting unit. Due to the nonlinearity and high-speed intermittent motion mode of a servomotor, the existing control technology is difficult to apply to the cutting system. This article presents a multimotor linear velocity planning approach used to ensure synchronous and cooperative operation of the motors in the cutting system. To achieve fast and accurate positioning control of the main drive motor running in fast acceleration and deceleration, periodic and intermittent mode, an adaptive position controller based on data-driven modeling technique is proposed, which makes the parameters of the controller change with the operation state of the main drive motor so that the controller can obtain good positioning accuracy in a wide working range of the main drive motor. Two linear models are established to represent the relationship between the positioning error and the positioning controller parameters and the main drive motor running conditions. The parameters of the two models are estimated offline and the parameters of the adaptive position controller can be obtained online quickly. Thus, the proposed control method for the main drive motor can be easily realized by general PLC in practical application. Simulation study results show that using the proposed method, the positioning error of the main drive motor is less than 0.1 mm when cutting 89-mm-long battery pole-piece and cutting 1 to 3 pieces/s. This result is much better than that of the position controller with fixed parameters.