Aranza, Muhammad Falah (2016) TUNING KONTROLER PID PADA SISTEM AVR DI CIRATA II DENGAN MENGGUNAKAN ALGORITMA PARTICLE SWARM OPTIMIZATION. S1 thesis, Universitas Pendidikan Indonesia.
|
Text
S_TE_1105051_Title.pdf Download (140kB) | Preview |
|
|
Text
S_TE_1105051_Abstract.pdf Download (211kB) | Preview |
|
|
Text
S_TE_1105051_Table_of_ontent.pdf Download (359kB) | Preview |
|
|
Text
S_TE_1105051_Chapter1.pdf Download (239kB) | Preview |
|
![[img]](http://repository.upi.edu/style/images/fileicons/text.png) |
Text
S_TE_1105051_Chapter2.pdf Restricted to Staf Perpustakaan Download (1MB) |
|
|
Text
S_TE_1105051_Chapter3.pdf Download (398kB) | Preview |
|
|
Text
S_TE_1105051_Chapter4.pdf Restricted to Staf Perpustakaan Download (796kB) |
|
|
Text
S_TE_1105051_Chapter5.pdf Download (247kB) | Preview |
|
|
Text
S_TE_1105051_Bibliography.pdf Download (273kB) | Preview |
|
|
Text
S_TE_1105051_Appendix.pdf Restricted to Staf Perpustakaan Download (317kB) |
Abstract
Pada skripsi ini membahas penerapan algoritma Particle Swarm Optimization dalam hal tuning kontroler PID pada sistem AVR (Automatic Voltage Regulator). Tuning kontroler PID atau mencari harga Kp (Konstanta Proportional), Ki (Konstanta Integral) dan Kd (Konstanta Derivative) yang optimal merupakan hal terpenting dalam PID karena tuning yang baik akan membuat performa dari kontroler PID menjadi optimal. Banyak metode tuning yang cukup terkenal antara lain, metode Ziegler-Nichols (ZN), Coheen COON, gain-phase margin dan Gain Scheduling. Akan tetapi, metode-metode tersebut dirasa kurang optimal untuk mengontrol sistem yang non linier dan memiliki orde tinggi, ditambah perhitungan dengan metode tersebut relatif sulit. Untuk mengatasi hal ini, algortima Particle Swarm Optimization (PSO) diusulkan untuk mendapatkan nilai Kp, Ki dan Kd yang optimal (Tuning). Pemilihan algoritma PSO dikarenakan PSO memiliki hasil yang memusat dan tidak memerlukan iterasi dengan jumlah yang banyak, sehingga perhitungannya relatif cepat. Berdasarkan hasil dari analisis transien, kestabilan Root Locus dan respon frekuensi, menunjukan bahwa tuning dengan menggunakan PSO memiliki hasil lebih baik dibanding dengan metode Ziegler-Nichols dan sistem tanpa kontroler PID. Kata kunci : AVR, PID, PSO, Analisis Transien, Root-Locus, Respon Frekuensi. In this paper explains applying Particle Swarm Optimization algorithm in tuning of PID controller on AVR (Automatic Voltage Regulator) system. Tuning in PID controller or search value Kp (Proportional Gain), Ki (Integral Gain) and Kd (Derivative Gain) that optimal is important in PID, because good tuning can yield performance of PID controller become maximal. Many methods that are enough familiar in tuning PID controller like Ziegler-Nichols (ZN) method, Cohen COON, gain-phase margin, Minimum Variance dan Gain Scheduling, however these methods are not optimal to control systems that nonlinear and have high-orde, in addition, in calculating of these methods relative difficult. To solve those obstacles, particle swarm optimization (PSO) algorithm is proposed to get Kp, Ki and Kd which optimal (Tuning). Choosing PSO is caused PSO has result of convergence and not require many iterations, so that in calculating relative quick. Based on result of analyzing transient, stability Root Locus and frequency response, show that tuning using PSO algorithm has result better than Ziegler-Nichols method and system without PID controller. Key words : AVR, PID, PSO, Transient Analyzing, Root-Locus, Frequency Response
| Item Type: | Thesis (S1) |
|---|---|
| Additional Information: | No. Panggil: S_TE_ARA t-2016; Pembimbing : I. Jaja Kustasa, II. Bambang |
| Uncontrolled Keywords: | AVR, PID, PSO, Analisis Transien, Root-Locus, Respon Frekuensi. |
| Subjects: | L Education > L Education (General) L Education > LB Theory and practice of education > LB1501 Primary Education Q Science > Q Science (General) |
| Divisions: | Fakultas Pendidikan Teknologi dan Kejuruan > Jurusan Pendidikan Teknik Elektro > Program Studi Pendidikan Teknik Elektro |
| Depositing User: | Mr. Cahya Mulyana |
| Date Deposited: | 11 Aug 2017 03:44 |
| Last Modified: | 11 Aug 2017 03:44 |
| URI: | http://repository.upi.edu/id/eprint/24762 |
Actions (login required)
 |
View Item |