DocumentCode :
2903579
Title :
A Novel attempt to reduce engineering effort in modeling non-linear chemical systems for Operator Training Simulators
Author :
Mukhopadhyay, Saibal ; Gundappa, Madhukar ; Srinivasan, Rajagopalan ; Narasimhan, Sriram
Author_Institution :
Dept. of Chem. Eng., IIT Madras, Chennai, India
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
1902
Lastpage :
1907
Abstract :
Operator Training Simulator (OTS) applications have become the norm of the industry in training operators to achieve efficient process operations. First principles based modeling approach in OTS packages achieves realistic simulations of chemical processes. However modeling the kinetics and thermodynamics accurately require considerable engineering efforts and may involve experimental studies to match the plant behavior. Hybrid models also known as grey-box models replace the unknown/complex equations in first principles models with empirical relationship using functional approximators such as neural networks, polynomials, etc. In this work we explore the use of Kernel Principal Component Analysis (K-PCA) as an approximation technique for certain nonlinear thermodynamics or kinetic functions parameterized using available plant archived data. Simulation results on a complex binary distillation column demonstrate the applicability of the proposed novel approach.
Keywords :
distillation; function approximation; principal component analysis; process control; thermodynamics; K-PCA; OTS package; approximation technique; complex binary distillation column; first principles based modeling; functional approximator; grey-box model; hybrid model; kernel principal component analysis; kinetic function; nonlinear chemical system; nonlinear thermodynamics; operator training simulator; Approximation methods; Data models; Equations; Kernel; Mathematical model; Principal component analysis; Steady-state; Grey-box models; Hybrid models; Kernel PCA;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
ISSN :
0743-1619
Print_ISBN :
978-1-4799-0177-7
Type :
conf
DOI :
10.1109/ACC.2013.6580113
Filename :
6580113
Link To Document :
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