Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/9233
Title: A learning scheme for low-speed precision tracking control of hybrid stepping motors
Authors: Chen, WD
Yung, KL 
Cheng, KW
Keywords: Hybrid stepping motor
Learning control system
Torque ripple
Tracking control
Issue Date: 2006
Source: IEEE/asme transactions on mechatronics, 2006, v. 11, no. 3, p. 362-365 How to cite?
Journal: IEEE/ASME Transactions on Mechatronics 
Abstract: Servo control of the hybrid stepping motor is complicated due to its highly nonlinear torque-current-position characteristics, especially under low operating speeds. This paper presents a simple and efficient control algorithm for the high-precision tracking control of hybrid stepping motors. The principles of learning control have been exploited to minimize the motor's torque ripple, which is periodic and nonlinear in the system states, with specific emphasis on low-speed situations. The proposed algorithm utilizes a fixed proportional-derivative (PD) feedback controller to stabilize the transient dynamics of the servomotor and the feedforward learning controller to compensate for the effect of the torque ripple and other disturbances for improved tracking accuracy. The stability and convergence performance of the learning control scheme is presented. It has been found that all error signals in the learning control system are bounded and the motion trajectory converges to the desired value asymptotically. The experimental results demonstrated the effectiveness and performance of the proposed algorithm.
URI: http://hdl.handle.net/10397/9233
ISSN: 1083-4435
DOI: 10.1109/TMECH.2006.875574
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

23
Last Week
0
Last month
0
Citations as of Sep 11, 2017

WEB OF SCIENCETM
Citations

17
Last Week
0
Last month
1
Citations as of Sep 15, 2017

Page view(s)

37
Last Week
1
Last month
Checked on Sep 18, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.