A New Linear Motor Force Ripple Compensation Method Based on Inverse Model Iterative Learning and Robust Disturbance Observer
Joint Authors
Yang, Xiaofeng
Fu, Xuewei
Chen, Zhenyu
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-02
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
Permanent magnet linear motors (PMLMs) are gaining increasing interest in ultra-precision and long stroke motion stage, such as reticle and wafer stage of scanner for semiconductor lithography.
However, the performances of PMLM are greatly affected by inherent force ripple.
A number of compensation methods have been studied to solve its influence to the system precision.
However, aiming at some application, the system characteristics limit the design of controller.
In this paper, a new compensation strategy based on the inverse model iterative learning control and robust disturbance observer is proposed to suppress the influence of force ripple.
The proposed compensation method makes fully use of not only achievable high tracking accuracy of the inverse model iterative learning control but also the higher robustness and better iterative learning speed by using robust disturbance observer.
Simulation and experiments verify effectiveness and superiority of the proposed method.
American Psychological Association (APA)
Fu, Xuewei& Yang, Xiaofeng& Chen, Zhenyu. 2018. A New Linear Motor Force Ripple Compensation Method Based on Inverse Model Iterative Learning and Robust Disturbance Observer. Complexity،Vol. 2018, no. 2018, pp.1-19.
https://search.emarefa.net/detail/BIM-1136842
Modern Language Association (MLA)
Fu, Xuewei…[et al.]. A New Linear Motor Force Ripple Compensation Method Based on Inverse Model Iterative Learning and Robust Disturbance Observer. Complexity No. 2018 (2018), pp.1-19.
https://search.emarefa.net/detail/BIM-1136842
American Medical Association (AMA)
Fu, Xuewei& Yang, Xiaofeng& Chen, Zhenyu. A New Linear Motor Force Ripple Compensation Method Based on Inverse Model Iterative Learning and Robust Disturbance Observer. Complexity. 2018. Vol. 2018, no. 2018, pp.1-19.
https://search.emarefa.net/detail/BIM-1136842
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1136842