Position Control Based on Add-on-Type Iterative Learning Control with Nonlinear Controller for Permanent-Magnet Stepper Motors
- Authors
- Suh, Sangmin; Kim, Wonhee
- Issue Date
- Jan-2021
- Publisher
- MDPI
- Keywords
- permanent-magnet stepper motor; position control
- Citation
- APPLIED SCIENCES-BASEL, v.11, no.2, pp 1 - 11
- Pages
- 11
- Journal Title
- APPLIED SCIENCES-BASEL
- Volume
- 11
- Number
- 2
- Start Page
- 1
- End Page
- 11
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/47668
- DOI
- 10.3390/app11020587
- ISSN
- 2076-3417
2076-3417
- Abstract
- In this paper, a current-error-based iterative learning controller (ILC) with a nonlinear controller is proposed to improve the position-tracking performance in permanent-magnet (PM) stepper motors. Our proposed method comprises a current-error-based ILC for mechanical dynamics and a nonlinear controller for current dynamics. A nonlinear controller using a variable structure is designed to obtain the field-oriented control. This nonlinear controller can cause the PM stepper motor become a single-input single-output linear system after finite time. The add-on-type ILC with proportional-integral control is designed to improve the position-tracking performance as the systems repeatedly perform the same operation. To increase the rate of error convergence, the current-error-based ILC is designed using the plant inversion method. The condition that the error converges to zero is mathematically derived. Thus, the proposed method can reduce the position-tracking error as the systems repeatedly perform the same operation. Furthermore, the proposed method can be easily plugged into the pre-designed controller. The performance of our proposed method was evaluated via simulations. In simulations, it is observed that the proposed method reduces the position-tracking error compared to the previous methods.
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Collections - College of Engineering > School of Energy System Engineering > 1. Journal Articles
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