Linear Parameter Varying (LPV) Model Identification on Primary Reformer Section of Ammonia Plant for Operator Training Simulator
| dc.contributor.author | Subagiyo, Heri | |
| dc.date.accessioned | 2014-12-03T08:17:58Z | |
| dc.date.available | 2014-12-03T08:17:58Z | |
| dc.date.issued | 2014-12-04 | |
| dc.identifier.citation | [1] Zhu, Yucai, Multivariable System Identification for Process Control, Oxford: Pergamon, 2001. [2] Erwin Hendarwin, Development of Operator Training Simulator for Ammonia Plant (Process Modeling, Control and Simulation), Master Thesis, Electrical Engineering Department, Institut Teknologi Bandung, Januari 2006. [3] J. Shamma and M. Athans, “Guaranteed properties of gain scheduled control for linear parameter varying plants”, Automatica, Vol. 27 No. 3, 1991, pp. 559-564. [4] J. Bokor and G. Balas, "Linear parameter varying systems: A geometric theory and applications", Preprints 16th IFAC World Congress, Prague, Czech Republic, July 2005, pp. 69-79. [5] B. Bamieh, L. Giarr´e, T. Raimondi, D. Bauso, M. Lodato and D. Rosa, “LPV Model Identification For The Stall And Surge Control Of Jet Engine”, 15th IFAC Symposium on Automatic Control in Aerospace, Bologna, Italy, September 2001. [6] H.Y Sutarto* and M.Fadly, “LPV Model Identification for Flutter Suppression Application”, Proc. of the 6th Asian Control Conference (ASCC), Bali, Indonesia, 2006. [7] B. Bamieh, L. Giarre, “Identification of Linear Parameter Varying Models”, International. Journal of Robust and Non-Linear Control, Vol. 12, 2002, pp. 841-853. [8] Nugraha B.E. Irianto, Kaltim-4 Ammonia Plant Operation Guide, PT. Pupuk Kalimantan Timur, Tbk, Bontang, 2002. [9] M. Nemani, R. Ravikanth, B.A. Bamieh, ”Identification of Linear Parametrically Varying Systems”, Proc. of the 34th IEEE Control and Decision Conference Vol. 3, New Orleans, Lousiana, December 1995, pp. 2990-2995. [10] L.H. Lee, K. Polla, “Identification of Linear Parameter-Varying Systems via LFTs”, Proc. of the 35th Conference on Decision and Control, Kobe, Japan, December 1996. [11] L. Ljung, System Identification Toolbox for Use with MATLAB, MathWorks Inc., Massachusetts, 2002. | en_US |
| dc.identifier.issn | 2407-4330 | |
| dc.identifier.uri | http://hdl.handle.net/11617/4992 | |
| dc.description.abstract | System or process identification is the field of mathematical modeling of systems (processes) from test or experimental data. Most of the existing works on process modeling were based on LTI (Linier Time Invariant) model. This paper presents the Linear Parameter Varying (LPV) model identification for primary reforming process in ammonia plant to cover changes in process operating conditions, such as start-up, normal operation and shut-down. Recursive Least Square (RLS) based algorithm with parameter function p =sin(0.0001*k) is employed in the identification process. Data needed for identification are taken from DCS historian data of the primary reformer process. The identification result is simulated and validated with the measured data. The process models obtained by this technique show reasonably fit with the mean value of 90.42 %. The process models are implemented on a simulation engine of Operator Training Simulator (OTS) using Scilab/Scicos software tools. Simulation result shows that the indicators of process variable mostly accepted. The mean value of deviations between process variables of simulated models and historian data are 10%, 20%, and 5%, for operation rate 40%, 65%, and 100%. | en_US |
| dc.publisher | Universitas Muhammadiyah Surakarta | en_US |
| dc.subject | Identification | en_US |
| dc.subject | Linear Parameter Varying (LPV) model | en_US |
| dc.subject | Primary Reformer | en_US |
| dc.subject | Operator Training Simulator (OTS) | en_US |
| dc.title | Linear Parameter Varying (LPV) Model Identification on Primary Reformer Section of Ammonia Plant for Operator Training Simulator | en_US |
| dc.type | Article | en_US |
