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Presentation
Sequential sub-problem programming strategies for data reconciliation and parameter estimation with multiple data sets
49th IEEE Conference on Decision and Control (2010)
  • Zhengjiang Zhang, Wenzhou University
  • Zhijiang Shao, Zhejiang University
  • Pengfei Jiang, Zhejiang University
  • Xi Chen, Zhejiang University
  • Yuhong Zhao, Zhejiang University
  • Jixin Qian, Zhejiang University
Abstract
Data reconciliation and parameter estimation (DRPE) is a key problem in real-time optimization. The dimensionality of the DRPE problem increases directly with the number of data sets, and the number of degrees of freedom in DRPE is very large. Therefore, solving a DRPE problem is very difficult. Sequential sub-problem programming strategies for data reconciliation and parameter estimation with multiple data sets are proposed in this paper. Based on the characteristics of a DRPE optimization problem, we construct a series of sub-problems depending on objective and model parameters. The solutions of each sub-problem are a good initial guess of the optimum of the next sub-problem. By solving the series of sub-problems, the optimum of the DRPE optimization problem can be derived. The proposed sequential sub-problem programming strategies are used in the industrial purified terephthalic acid (PTA) oxidation process system. The effectiveness of the proposed strategies is demonstrated by the results of numerical experiments.
Publication Date
2010
Citation Information
Zhengjiang Zhang, Zhijiang Shao, Pengfei Jiang, Xi Chen, et al.. "Sequential sub-problem programming strategies for data reconciliation and parameter estimation with multiple data sets" 49th IEEE Conference on Decision and Control (2010)
Available at: http://works.bepress.com/zhengjiang_zhang/6/