Tian_Xia_Yu_Yang_IEEE_SMC_2006.pdf (855.02 kB)
Non-linear dynamic data reconciliation for industrial processes
conference contribution
posted on 2009-01-28, 11:32 authored by Xuemin Tian, Bokai Xia, Zuojun Yu, Shuang-Hua YangThis paper investigates and improves a technique
known as Nonlinear Dynamic Data Reconciliation (NDDR) for a
real industrial process. NDDRS is a technique for data
reconciliation that requires an objective function to be
minimised subject to both algebraic and differential, equality
and inequality constraints. These constraints are obtained from
the mathematical description of the process and ensure that the
measurement data can be optimised to conform as closely as
possible to the true behaviour of the process. One of the
difficulties of using the original NDDR is that a rigorous process
dynamic model is required as a constraint. Unfortunately it is
very hard to establish a rigorous dynamic model for a complex
industrial process, particularly for data reconciliation purpose.
A transfer function matrix model has been introduced in this
new NDDR method. Therefore the rigorous dynamic model is
avoided. The real industrial data from FCCU is used to
illustrate the efficiency of the new NDDR method.
History
School
- Science
Department
- Computer Science
Citation
TIAN, X....et al., 2006. Non-linear dynamic data reconciliation for industrial processes. IN: IEEE International Conference on Systems, Man and Cybernetics, (SMC '06), 8-11 Oct., Taipai, Taiwan, Vol. 6, pp. 5291 - 5296.Publisher
© IEEEVersion
- VoR (Version of Record)
Publication date
2006Notes
This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.ISBN
1424400996Language
- en