DocumentCode :
2902113
Title :
Improvements in the motion accuracy of Linear Switched Reluctance Motors
Author :
San-Chin Kwok, Antares ; Gan, Wai-Chuen ; Cheung, Norbert C.
Author_Institution :
ASM Assembly Autom. Hong Kong Ltd., Kwai Chung
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
1
Lastpage :
10
Abstract :
During the last decade, the linear switched reluctance motor (LSRM) has become popular due to its structural simplicity, robustness and high power density. However, its significant torque ripple creates difficulty on precision motion control. This paper aims to develop a robust control system to improve the motion accuracy of LSRMs. The LSRM prototype is firstly investigated to study its force and current relationship. With the help of software, LSRM motion tests are simulated before real experiment. The significant improvement on position control strongly proves the success of the proposal. After that, the experimental result applying on the real prototype closely matches the simulation result. In order to enhance the LSRM robustness and the position tracking responses, another fuzzy logic controller is newly designed and implemented to supervise the traditional proportional-differential (PD) control parameters. Combining the inner control loop on current force relationship and the outer control loop on PD parameter supervision, the LSRM system in this project is very robust and capable to provide a high precision motion performance.
Keywords :
PD control; fuzzy control; linear motors; machine control; motion control; reluctance motors; robust control; fuzzy logic controller; inner control loop; linear switched reluctance motors; motion accuracy; motion control; proportional-differential control; robust control system; structural simplicity; Control systems; Force control; Motion control; PD control; Proportional control; Prototypes; Reluctance motors; Robust control; Robustness; Software prototyping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1098-7584
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZY.2008.4630334
Filename :
4630334
Link To Document :
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