Extended state observer–based fractional order proportional–derivative controller for precision trajectory tracking control of a novel linear motor

Author:

Shi Xinxin1,Huang Jiacai1,Li Hongsheng1

Affiliation:

1. School of Automation, Nanjing Institute of Technology, Nanjing, P.R. China

Abstract

An extended state observer–based fractional order proportional–derivative controller is presented to realize precision trajectory tracking control of a novel linear motor in this article. Structure, working principle, and mathematical model of the linear motor are demonstrated. Fractional order calculus, extended state observer, proportional–derivative control, and feedforward control are combined to accomplish high trajectory tracking accuracy. Comparative simulations and experimental results indicate that the proposed controller is robust to parameter variations and uncertain disturbances, and high tracking performance of the novel linear motor for different desired sinusoidal trajectories has been obtained.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Control and Systems Engineering

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Behavioral Study of Different Controllers and Algorithms in Real-Time Applications;IETE Journal of Research;2022-12-20

2. A New Active Disturbance Controller Based on an Improved Fraction-Order Extended State Observer;2021 4th International Conference on Robotics, Control and Automation Engineering (RCAE);2021-11-04

3. A Fractional-Order Active Disturbance Rejection Controller Design for a PMSM Servo System;2021 4th International Conference on Mechatronics, Robotics and Automation (ICMRA);2021-10-22

4. Force ripple compensation of the directly-driven linear motors via iterative tuning feed-forward controller;Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering;2019-02-07

5. Application of fractional-order active disturbance rejection controller on linear motion system;Control Engineering Practice;2018-12

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