OPTIMISASI KONTROL PID UNTUK MOTOR DC MAGNET PERMANEN MENGGUNAKAN PARTICLE SWARM OPTIMIZATION
To maximize the performance of DC motors, the proper use of the controller is crucial. Design of Proportional Integral Derivative (PID) controller on dc motor has been done frequently. The use of PID controllers requires proper parameter setting to achieve optimal performance on the motor. Commonly...
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Sekolah Tinggi Manajemen Informatika dan Komputer (STMIK) Pringsewu
2017-12-01
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doaj-7a0d9a0a50ef4771accfdc86212deeca2020-11-25T01:22:04ZindSekolah Tinggi Manajemen Informatika dan Komputer (STMIK) PringsewuJurnal TAM2339-11032579-42212017-12-0182117122521OPTIMISASI KONTROL PID UNTUK MOTOR DC MAGNET PERMANEN MENGGUNAKAN PARTICLE SWARM OPTIMIZATIONMuhammad Ruswandi Djalal0Rahmat Rahmat1Jurusan Teknik Mesin, Program Studi Teknik Energi, Politeknik Negeri Ujung PandangJurusan Teknik Mesin, Program Studi Teknik Energi, Politeknik Negeri Ujung PandangTo maximize the performance of DC motors, the proper use of the controller is crucial. Design of Proportional Integral Derivative (PID) controller on dc motor has been done frequently. The use of PID controllers requires proper parameter setting to achieve optimal performance on the motor. Commonly used is the trial-error method, to determine the parameters of the PID controller, but the results obtained do not make the PID controller optimal and will actually damage the system. Therefore, in this research we will propose one of PID parameter tuning method, that is by using Particle Swarm Optimization (PSO), to optimize and determine the proper parameters of PID. PSO is one of the smart methods inspired by the behavior of particles that search for food sources in groups, this concept is adapted and applied into intelligent algorithms to solve optimization problems. From the results obtained the PSO method can well tune the parameters of PID, where for Kp 57.2409, ki = 23.7090, and kd = 9.3575. Response speed after PID receiver, resulting overshoot does not exist and settling time is very fast.http://ojs.stmikpringsewu.ac.id/index.php/JurnalTam/article/view/539PID, Particle Swarm Optimization, Settling Time, Trial Error |
collection |
DOAJ |
language |
Indonesian |
format |
Article |
sources |
DOAJ |
author |
Muhammad Ruswandi Djalal Rahmat Rahmat |
spellingShingle |
Muhammad Ruswandi Djalal Rahmat Rahmat OPTIMISASI KONTROL PID UNTUK MOTOR DC MAGNET PERMANEN MENGGUNAKAN PARTICLE SWARM OPTIMIZATION Jurnal TAM PID, Particle Swarm Optimization, Settling Time, Trial Error |
author_facet |
Muhammad Ruswandi Djalal Rahmat Rahmat |
author_sort |
Muhammad Ruswandi Djalal |
title |
OPTIMISASI KONTROL PID UNTUK MOTOR DC MAGNET PERMANEN MENGGUNAKAN PARTICLE SWARM OPTIMIZATION |
title_short |
OPTIMISASI KONTROL PID UNTUK MOTOR DC MAGNET PERMANEN MENGGUNAKAN PARTICLE SWARM OPTIMIZATION |
title_full |
OPTIMISASI KONTROL PID UNTUK MOTOR DC MAGNET PERMANEN MENGGUNAKAN PARTICLE SWARM OPTIMIZATION |
title_fullStr |
OPTIMISASI KONTROL PID UNTUK MOTOR DC MAGNET PERMANEN MENGGUNAKAN PARTICLE SWARM OPTIMIZATION |
title_full_unstemmed |
OPTIMISASI KONTROL PID UNTUK MOTOR DC MAGNET PERMANEN MENGGUNAKAN PARTICLE SWARM OPTIMIZATION |
title_sort |
optimisasi kontrol pid untuk motor dc magnet permanen menggunakan particle swarm optimization |
publisher |
Sekolah Tinggi Manajemen Informatika dan Komputer (STMIK) Pringsewu |
series |
Jurnal TAM |
issn |
2339-1103 2579-4221 |
publishDate |
2017-12-01 |
description |
To maximize the performance of DC motors, the proper use of the controller is crucial. Design of Proportional Integral Derivative (PID) controller on dc motor has been done frequently. The use of PID controllers requires proper parameter setting to achieve optimal performance on the motor. Commonly used is the trial-error method, to determine the parameters of the PID controller, but the results obtained do not make the PID controller optimal and will actually damage the system. Therefore, in this research we will propose one of PID parameter tuning method, that is by using Particle Swarm Optimization (PSO), to optimize and determine the proper parameters of PID. PSO is one of the smart methods inspired by the behavior of particles that search for food sources in groups, this concept is adapted and applied into intelligent algorithms to solve optimization problems. From the results obtained the PSO method can well tune the parameters of PID, where for Kp 57.2409, ki = 23.7090, and kd = 9.3575. Response speed after PID receiver, resulting overshoot does not exist and settling time is very fast. |
topic |
PID, Particle Swarm Optimization, Settling Time, Trial Error |
url |
http://ojs.stmikpringsewu.ac.id/index.php/JurnalTam/article/view/539 |
work_keys_str_mv |
AT muhammadruswandidjalal optimisasikontrolpiduntukmotordcmagnetpermanenmenggunakanparticleswarmoptimization AT rahmatrahmat optimisasikontrolpiduntukmotordcmagnetpermanenmenggunakanparticleswarmoptimization |
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1725128022958276608 |