Adaptive Fuzzy Sliding Mode Position Control of a Brushless DC Motor
碩士 === 中原大學 === 電機工程研究所 === 91 === Investigated in this thesis is the feasibility of using Fuzzy Sliding Mode controller (FSMC) for position control of DC brushless rotary Motor. The parameters of DC brushless rotary Motor will change slightly with different input command. And FSMC can achieve good...
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ndltd-TW-091CYCU54420112018-06-25T06:06:26Z http://ndltd.ncl.edu.tw/handle/445a3w Adaptive Fuzzy Sliding Mode Position Control of a Brushless DC Motor 直流無刷馬達之適應性模糊滑動模式位置控制 I-Shun Dong 董義雄 碩士 中原大學 電機工程研究所 91 Investigated in this thesis is the feasibility of using Fuzzy Sliding Mode controller (FSMC) for position control of DC brushless rotary Motor. The parameters of DC brushless rotary Motor will change slightly with different input command. And FSMC can achieve good output response even when the plant model has some uncertainty. The structure of the control algorithm in this thesis is to combine fuzzy control with sliding mode control. And in the optimization part of the control algorithm, the 3*3 fuzzy rule base and the gains of the control algorithm are searched simultaneously through adaptive genetic algorithm (AGA), whose adaptive crossover rate and mutation rate can avoid falling into local optimum and speed up the convergence. The simulation part of the control algorithm design is done through the software of Matlab/Simulink. As for the experiment part, we use the DC brushless rotary Motor, power amplifier and TI DSP (TMS320 F243) controller supported by Juniortek to verify and improve the feasibility of controller. The results show that, FSMC is highly robust even when the plant model has some uncertainty, and the optimal FSMC designed by AGA can track position command rapidly. LAI LIN-YING 賴玲瑩 2003 學位論文 ; thesis 90 zh-TW |
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碩士 === 中原大學 === 電機工程研究所 === 91 === Investigated in this thesis is the feasibility of using Fuzzy Sliding Mode controller (FSMC) for position control of DC brushless rotary Motor. The parameters of DC brushless rotary Motor will change slightly with different input command. And FSMC can achieve good output response even when the plant model has some uncertainty. The structure of the control algorithm in this thesis is to combine fuzzy control with sliding mode control. And in the optimization part of the control algorithm, the 3*3 fuzzy rule base and the gains of the control algorithm are searched simultaneously through adaptive genetic algorithm (AGA), whose adaptive crossover rate and mutation rate can avoid falling into local optimum and speed up the convergence. The simulation part of the control algorithm design is done through the software of Matlab/Simulink. As for the experiment part, we use the DC brushless rotary Motor, power amplifier and TI DSP (TMS320 F243) controller supported by Juniortek to verify and improve the feasibility of controller. The results show that, FSMC is highly robust even when the plant model has some uncertainty, and the optimal FSMC designed by AGA can track position command rapidly.
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author2 |
LAI LIN-YING |
author_facet |
LAI LIN-YING I-Shun Dong 董義雄 |
author |
I-Shun Dong 董義雄 |
spellingShingle |
I-Shun Dong 董義雄 Adaptive Fuzzy Sliding Mode Position Control of a Brushless DC Motor |
author_sort |
I-Shun Dong |
title |
Adaptive Fuzzy Sliding Mode Position Control of a Brushless DC Motor |
title_short |
Adaptive Fuzzy Sliding Mode Position Control of a Brushless DC Motor |
title_full |
Adaptive Fuzzy Sliding Mode Position Control of a Brushless DC Motor |
title_fullStr |
Adaptive Fuzzy Sliding Mode Position Control of a Brushless DC Motor |
title_full_unstemmed |
Adaptive Fuzzy Sliding Mode Position Control of a Brushless DC Motor |
title_sort |
adaptive fuzzy sliding mode position control of a brushless dc motor |
publishDate |
2003 |
url |
http://ndltd.ncl.edu.tw/handle/445a3w |
work_keys_str_mv |
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