Fauzi, M. Razan Ridho (2021) Desain Model Predictive Control Pada Main Cryogenic Heat Exchanger Di Proses Liquefaction Natural Gas. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Gas alam merupakan energi paling efisien dengan tingkat emisi paling rendah dibandingkan energi fossil lain. Pada proses pendinginan gas alam, salah satu equipment yang paling penting adalah Main Cryogenic Heat Exchanger. Proses pendinginan gas alam pada MCHE dilakukan dengan mengalirkan Mixed Component Refrigerant (MCR) yang berperan sebagai
fluida pendingin dan aliran gas alam sebagai fluida panas. Multivariable Model Predictive Control (MMPC) digunakan untuk mengendalikan proses MCHE dengan tujuan untuk
menangkap fenomena interaksi antar variabel dalam proses untuk meningkatkan kinerja pengendalian. Karena proses terdiri dari 2 variabel input dan 2 variabel output, MMPC (2X2) digunakan dalam penelitian ini. Interaksi ntarvariable ditunjukkan pada matrix 2x2 dimana setiap elemen matriks adalah model First Order Plus Dead Time (FOPDT). dentifikasi
proses model FOPDT didapatkan dengan melakukan uji open loop dan uji set point pada tiap hubungan interaksi antara Manipulated Variable dan Controled Variable. Pengujian MMPC
(2X2) dilakukan dengan melakukan uji perubahan set point (SP) dan respon terhadap gangguan. Indikator yang mengukur kinerja pengendali adalah Integral Absolute Error (IAE) dan Error Steady State (ESS). Selain itu, untuk mengetahui kemajuan dari kinerja pengendalian, dilakukan juga perbandingan respon sistem dengan tipe kontrol PID. Hasil
penelitian menunjukkan bahwa MMPC (2X2) lebih baik dari PID baik di IAE maupun ESS. Hal ini ditunjukkan dengan peningkatan sebesar signifikan pada nilai IAE dan ESS dengan nilai ESS pada MPC bernilai dibawah batas error toleransi yaitu 2%.
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Natural gas is the most efficient fossil energy with the lowest emission levels compared to other fossil energies. In the natural gas cooling process, one of the most important
equipment is the Main Cryogenic Heat Exchange (MCHE). The natural gas cooling process at MCHE is carried out by flowing Mixed Component Refrigerant (MCR) which acts as
cooling fluid and natural gas fluid as hot fluid. multivariable Model Predictive Control
(MMPC) is used to control the MCHE process with the aim to capture phenomenon of interaction between variables in the process to improve control peformance. The process
consists of 2 input variables and 2 output variable. Therefore, MMPC (2X2) was used in this study. The interaction between variables is shown in a 2x2 matrix where each matrix element is a First Order Plus Dead Time (FOPDT) model. The FOPDT system identification was obtained by peforming open loop and set point test on each interaction between Mainpulated Variable and Controled Variable.The MMPC (2X2) peformance was tested by set point change test and disturbance test. Indicators that measure control peformance are Integral Absolute Error (IAE) and Error Steady State (ESS). In addition, to determine the improvement of the control peformance, a comparison of the response system with the PID control was also carried out. The results showed that MMPC (2X2) was better than PID in both IAE and ESS. The statement was proved by value of MPC ESS and IAE shows
significant improvement and the ESS value of MPC is below error tolerance which is 2%.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | model predictive control, multivariable, process model, mche |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK4035.R4 Refrigeration and refrigerating machinery T Technology > TP Chemical technology > TP492.3 Refrigeration and refrigerating machinery T Technology > TP Chemical technology > TP692.5 Oil and gasoline handling and storage |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | M. Razan Ridho Fauzi |
| Date Deposited: | 31 Aug 2021 23:14 |
| Last Modified: | 17 Jan 2024 00:44 |
| URI: | http://repository.its.ac.id/id/eprint/90976 |
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