Volume 32, Issue 2, September 2017, Pages 251–264
Anuj Abraham1, V. Vetriselvi2, and N. Pappa3
1 Department of Applied Electronics & Instrumentation, Rajagiri School of Engineering & Technology, APJ Abdul Kalam Technological University, Kerala, India
2 Department of Instrumentation Engineering, MIT Campus, Anna University, Chennai, India
3 Department of Instrumentation Engineering, MIT Campus, Anna University, Chennai, India
Original language: English
Copyright © 2017 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In this paper, an optimal Generalized Predictive Control (GPC) is developed for binary distillation column using first principle model and linearized models. The nonlinear multivariable binary distillation column process is simulated with first principle differential equations and its linearized 16th order and reduced 5th order models were obtained. The GPC is designed based on original linearized model, reduced model and nonlinear first principle model. The performance of GPC with the above three considered model structures were compared. The response of GPC with reduced 5th order model shows similar characteristics of linearized 16th order model. Hence, the computation complexity can be reduced using a reduced order model for a binary distillation column process, without compromising on the performance.
Author Keywords: Binary distillation column, multivariable, reduced order, modeling, linearization, generalized predictive controller.
Anuj Abraham1, V. Vetriselvi2, and N. Pappa3
1 Department of Applied Electronics & Instrumentation, Rajagiri School of Engineering & Technology, APJ Abdul Kalam Technological University, Kerala, India
2 Department of Instrumentation Engineering, MIT Campus, Anna University, Chennai, India
3 Department of Instrumentation Engineering, MIT Campus, Anna University, Chennai, India
Original language: English
Copyright © 2017 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In this paper, an optimal Generalized Predictive Control (GPC) is developed for binary distillation column using first principle model and linearized models. The nonlinear multivariable binary distillation column process is simulated with first principle differential equations and its linearized 16th order and reduced 5th order models were obtained. The GPC is designed based on original linearized model, reduced model and nonlinear first principle model. The performance of GPC with the above three considered model structures were compared. The response of GPC with reduced 5th order model shows similar characteristics of linearized 16th order model. Hence, the computation complexity can be reduced using a reduced order model for a binary distillation column process, without compromising on the performance.
Author Keywords: Binary distillation column, multivariable, reduced order, modeling, linearization, generalized predictive controller.
How to Cite this Article
Anuj Abraham, V. Vetriselvi, and N. Pappa, “Reduced Order Model Based GPC for a Binary Distillation Column,” International Journal of Innovation and Scientific Research, vol. 32, no. 2, pp. 251–264, September 2017.
