PPMLM direct thrust force control based on iterative learning high‐order improved model free adaptive control

• Published in: IET renewable power generation Vol. 18; no. 9-10; pp. 1661 - 1674
• Main Authors: Wang, Xiuping, Yao, Shunyu, Qu, Chunyu
• Format: Journal Article
• Language: English
• Published: Wiley 01.07.2024
• Subjects: direct thrust force control; dynamic linearization; feedforward compensation; iterative learning control; load disturbances; model free adaptive control; primary permanent magnet linear motor
• ISSN: 1752-1416; 1752-1424
• DOI: 10.1049/rpg2.13013

A high‐order improved model free adaptive control method based on iterative learning is designed to address the problem that primary permanent magnet linear motor has poor control performance, susceptibilities to load disturbances and other nonlinear disturbances during operation. The proposed algorithm adopts an improved dynamic linearization model and high‐order pseudo partial derivative estimation algorithm, which improves the data utilization of the data‐driven control algorithm, makes the algorithm better to describe the dynamic behaviour of the primary permanent magnet linear motor direct thrust force control system and improves the speed tracking accuracy and anti‐interference ability of the system. In addition, iterative learning control was adopted as feedforward compensation to further improve the control performance of the system and the stability of the closed‐loop system was analysed analytically. The simulation results show that the proposed control algorithm can improve the control accuracy of the system and suppress load disturbances and other nonlinear disturbances. In this article, a data driven speed controller is designed for the primary permanent magnet linear motor control system, which is vulnerable to the influence of nonlinear factors such as parameter time‐varying, load disturbance, end effect and so on. To suppress the influence of various nonlinear disturbances on the control accuracy of the control system. The iterative learning high‐order improved model free adaptive control in the data driven control is applied to the primary permanent magnet linear motor direct thrust force control system, the nonlinear disturbance is suppressed, the speed control accuracy is improved and the thrust fluctuation is reduced. The simulation results show that the proposed method is effective.