PID Controller Tuning Based on Particle Swarm Optimization (PSO) for Stewart Platform
碩士 === 國立高雄第一科技大學 === 系統資訊與控制研究所 === 98 === In this study, we used Particle Swarm Optimization (PSO) to tune the parameters of PID controller. Some error-criteria are the fitness function, the performance index, are used to judge the performances. The performance index have three functions: (1) The...
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ndltd-TW-098NKIT53920172016-04-20T04:17:31Z http://ndltd.ncl.edu.tw/handle/40033895948135769173 PID Controller Tuning Based on Particle Swarm Optimization (PSO) for Stewart Platform 基於粒子群聚最佳化PID參數於史都華平台控制器之應用 Ming-Tung Liu 劉銘統 碩士 國立高雄第一科技大學 系統資訊與控制研究所 98 In this study, we used Particle Swarm Optimization (PSO) to tune the parameters of PID controller. Some error-criteria are the fitness function, the performance index, are used to judge the performances. The performance index have three functions: (1) The integral square error criterion (ISE) (2) The integral absolute error criterion (IAE) (3) The integral time absolute error criterion (ITAE). Otherwise, the “open loop testing method” and “trial and error method” are employed to obtain the transfer function of Stewart platform. In order to take optimum parameters of PID controller, the PSO algorithm be used and results are compared with traditional Z-N tuning rule. Finally, the experimental results verify the PID parameters based on PSO algorithm not only keep system stable, but also decrease overshoot. Chin-I Huang 黃勤鎰 2010 學位論文 ; thesis 105 zh-TW |
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碩士 === 國立高雄第一科技大學 === 系統資訊與控制研究所 === 98 === In this study, we used Particle Swarm Optimization (PSO) to tune the parameters of PID controller. Some error-criteria are the fitness function, the performance index, are used to judge the performances. The performance index have three functions: (1) The integral square error criterion (ISE) (2) The integral absolute error criterion (IAE) (3) The integral time absolute error criterion (ITAE).
Otherwise, the “open loop testing method” and “trial and error method” are employed to obtain the transfer function of Stewart platform. In order to take optimum parameters of PID controller, the PSO algorithm be used and results are compared with traditional Z-N tuning rule. Finally, the experimental results verify the PID parameters based on PSO algorithm not only keep system stable, but also decrease overshoot.
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author2 |
Chin-I Huang |
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Chin-I Huang Ming-Tung Liu 劉銘統 |
author |
Ming-Tung Liu 劉銘統 |
spellingShingle |
Ming-Tung Liu 劉銘統 PID Controller Tuning Based on Particle Swarm Optimization (PSO) for Stewart Platform |
author_sort |
Ming-Tung Liu |
title |
PID Controller Tuning Based on Particle Swarm Optimization (PSO) for Stewart Platform |
title_short |
PID Controller Tuning Based on Particle Swarm Optimization (PSO) for Stewart Platform |
title_full |
PID Controller Tuning Based on Particle Swarm Optimization (PSO) for Stewart Platform |
title_fullStr |
PID Controller Tuning Based on Particle Swarm Optimization (PSO) for Stewart Platform |
title_full_unstemmed |
PID Controller Tuning Based on Particle Swarm Optimization (PSO) for Stewart Platform |
title_sort |
pid controller tuning based on particle swarm optimization (pso) for stewart platform |
publishDate |
2010 |
url |
http://ndltd.ncl.edu.tw/handle/40033895948135769173 |
work_keys_str_mv |
AT mingtungliu pidcontrollertuningbasedonparticleswarmoptimizationpsoforstewartplatform AT liúmíngtǒng pidcontrollertuningbasedonparticleswarmoptimizationpsoforstewartplatform AT mingtungliu jīyúlìziqúnjùzuìjiāhuàpidcānshùyúshǐdōuhuápíngtáikòngzhìqìzhīyīngyòng AT liúmíngtǒng jīyúlìziqúnjùzuìjiāhuàpidcānshùyúshǐdōuhuápíngtáikòngzhìqìzhīyīngyòng |
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1718227469667926016 |