Multivariable System Identification of a Continuous Binary Distillation Column
Distillation is a process that is commonly used in industries for separation purpose. A distillation column is a multivariable system which shows nonlinear dynamic behavior due to its nonlinear vapor-liquid equilibrium. In order to gain better product quality and lower energy consumption of the d...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | en |
| Published: |
2011
|
| Subjects: | |
| Online Access: | http://utpedia.utp.edu.my/id/eprint/6708/1/2011%20Master%20-%20Multivariable%20System%20Identification%20of%20a%20Continuous%20Binary%20Distillation%20Column.pdf http://utpedia.utp.edu.my/id/eprint/6708/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1833328436067696640 |
|---|---|
| author | BALOCH, MOHAMMAD ADNAN |
| author_facet | BALOCH, MOHAMMAD ADNAN |
| author_sort | BALOCH, MOHAMMAD ADNAN |
| building | UTP Resource Centre |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Petronas |
| content_source | UTP Electronic and Digitized Intellectual Asset |
| continent | Asia |
| country | Malaysia |
| description | Distillation is a process that is commonly used in industries for separation purpose. A
distillation column is a multivariable system which shows nonlinear dynamic
behavior due to its nonlinear vapor-liquid equilibrium. In order to gain better product
quality and lower energy consumption of the distillation column, an effective model
based control system is needed to allow the process to be operated over a certain
operating range. In control engineering, System Identification is considered as a well
suited approach for developing an approximate model for the nonlinear system. In this
study, System Identification technique is applied to predict the top and bottom
product composition by focusing the temperature of the distillation column. The
process in the column is based on the distillation of a binary mixture of Isopropyl
Alcohol and Acetone. The experimental data obtained from the distillation column
was used for estimation and validation of simulated models. During analysis, different
types of linear and nonlinear models were developed and are compared to predict the
best model which can be effectively used for designing the control system of the
distillation column. Among the linear models such as; Autoregressive with
Exogenous Input (ARX), Autoregressive Moving Average with Exogenous inputs
(ARMAX), Linear State Space (LSS) model and Continuous Process Model were
developed and compared with each other. The results of this comparison reveals that
the perf01mance of LSS model is efficient and hence it was further used to improve
the modeling approach and compared with other nonlinear models. A Nonlinear State
Space (NSS) model was developed by the combination of LSS and Neural Network
(NN) and is compared solely with NN and ANFIS identification model. The
simulation results show that the developed NSS model is well capable of defining the
dynan1ics of the plant based on the best fit criteria and residual performance. In
addition to this, NSS model predicted the best statistical measurement of the nonlinear
system. This approach is helpful for designing the efficient control system for online
separation process of the plant. |
| format | Thesis |
| id | oai:utpedia.utp.edu.my:6708 |
| institution | Universiti Teknologi Petronas |
| language | en |
| publishDate | 2011 |
| record_format | eprints |
| spelling | oai:utpedia.utp.edu.my:67082017-01-25T09:41:56Z http://utpedia.utp.edu.my/id/eprint/6708/ Multivariable System Identification of a Continuous Binary Distillation Column BALOCH, MOHAMMAD ADNAN TK Electrical engineering. Electronics Nuclear engineering Distillation is a process that is commonly used in industries for separation purpose. A distillation column is a multivariable system which shows nonlinear dynamic behavior due to its nonlinear vapor-liquid equilibrium. In order to gain better product quality and lower energy consumption of the distillation column, an effective model based control system is needed to allow the process to be operated over a certain operating range. In control engineering, System Identification is considered as a well suited approach for developing an approximate model for the nonlinear system. In this study, System Identification technique is applied to predict the top and bottom product composition by focusing the temperature of the distillation column. The process in the column is based on the distillation of a binary mixture of Isopropyl Alcohol and Acetone. The experimental data obtained from the distillation column was used for estimation and validation of simulated models. During analysis, different types of linear and nonlinear models were developed and are compared to predict the best model which can be effectively used for designing the control system of the distillation column. Among the linear models such as; Autoregressive with Exogenous Input (ARX), Autoregressive Moving Average with Exogenous inputs (ARMAX), Linear State Space (LSS) model and Continuous Process Model were developed and compared with each other. The results of this comparison reveals that the perf01mance of LSS model is efficient and hence it was further used to improve the modeling approach and compared with other nonlinear models. A Nonlinear State Space (NSS) model was developed by the combination of LSS and Neural Network (NN) and is compared solely with NN and ANFIS identification model. The simulation results show that the developed NSS model is well capable of defining the dynan1ics of the plant based on the best fit criteria and residual performance. In addition to this, NSS model predicted the best statistical measurement of the nonlinear system. This approach is helpful for designing the efficient control system for online separation process of the plant. 2011-08 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/id/eprint/6708/1/2011%20Master%20-%20Multivariable%20System%20Identification%20of%20a%20Continuous%20Binary%20Distillation%20Column.pdf BALOCH, MOHAMMAD ADNAN (2011) Multivariable System Identification of a Continuous Binary Distillation Column. Masters thesis, Universiti Teknologi Petronas. |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering BALOCH, MOHAMMAD ADNAN Multivariable System Identification of a Continuous Binary Distillation Column |
| title | Multivariable System Identification of a Continuous Binary
Distillation Column |
| title_full | Multivariable System Identification of a Continuous Binary
Distillation Column |
| title_fullStr | Multivariable System Identification of a Continuous Binary
Distillation Column |
| title_full_unstemmed | Multivariable System Identification of a Continuous Binary
Distillation Column |
| title_short | Multivariable System Identification of a Continuous Binary
Distillation Column |
| title_sort | multivariable system identification of a continuous binary
distillation column |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://utpedia.utp.edu.my/id/eprint/6708/1/2011%20Master%20-%20Multivariable%20System%20Identification%20of%20a%20Continuous%20Binary%20Distillation%20Column.pdf http://utpedia.utp.edu.my/id/eprint/6708/ |
| url_provider | http://utpedia.utp.edu.my/ |