Heuristic scaling method for efficient parameter estimation

被引:1
作者
Yang, Kyung-won [2 ]
Lee, Tai-yong [1 ,2 ]
机构
[1] Hongik Univ, Dept Chem Engn, Seoul 121791, South Korea
[2] Korea Adv Inst Sci & Technol, Dept Chem & Biomol Engn, Taejon 305701, South Korea
关键词
Scaling factor; Condition number; Parameter estimation; Hessian matrix; MODELS; ALGORITHM;
D O I
10.1016/j.cherd.2009.09.017
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In parameter estimation, an order-of-magnitude difference in parameter values makes it difficult to find the optimum because parameter estimation problem can be ill-conditioned by the difference. To avoid the difficulty, a proper scaling factor of parameter should be introduced into parameter estimation. Unfortunately there has not been an appropriate method for determining a set of scaling factor. In this work, we propose a new heuristic method for determining the scaling factor which converts parameter estimation problem well-conditioned. The proposed method provides a set of scaling factor to reduce the condition number of Hessian matrix since the small value of condition number is directly related to the conditions of the problem. Numerical implementation demonstrated that the proposed method drastically enhanced the solvability of original ill-conditioned problem. (C) 2009 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:520 / 528
页数:9
相关论文
共 20 条
  • [1] Computation of optimal identification experiments for nonlinear dynamic process models: a stochastic global optimization approach
    Banga, JR
    Versyck, KJ
    Van Impe, JF
    [J]. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2002, 41 (10) : 2425 - 2430
  • [2] Bard Y., 1974, Nonlinear parameter estimation
  • [3] Bates D. M., 1988, Nonlinear regression analysis and its applications, V2
  • [4] Beck J.V., 1977, Parameter estimation in engineering and science
  • [5] NONLINEAR PARAMETER-ESTIMATION - A CASE-STUDY COMPARISON
    BIEGLER, LT
    DAMIANO, JJ
    BLAU, GE
    [J]. AICHE JOURNAL, 1986, 32 (01) : 29 - 45
  • [6] DENNIS J. E., 1996, Numerical Methods for Unconstrained Optimization and Nonlinear Equations
  • [7] Kinetic parameter estimation from TGA: Optimal design of TGA experiments
    Dirion, Jean-Louis
    Reverte, Cedric
    Cabassud, Michel
    [J]. CHEMICAL ENGINEERING RESEARCH & DESIGN, 2008, 86 (6A) : 618 - 625
  • [8] Horn R. A., 1999, MATRIX ANAL
  • [9] IMPROVEMENT OF GAUSS-NEWTON METHOD FOR PARAMETER-ESTIMATION THROUGH THE USE OF INFORMATION INDEX
    KALOGERAKIS, N
    LUUS, R
    [J]. INDUSTRIAL & ENGINEERING CHEMISTRY FUNDAMENTALS, 1983, 22 (04): : 436 - 445
  • [10] A hybrid genetic algorithm for efficient parameter estimation of large kinetic models
    Katare, S
    Bhan, A
    Caruthers, JM
    Delgass, WN
    Venkatasubramanian, V
    [J]. COMPUTERS & CHEMICAL ENGINEERING, 2004, 28 (12) : 2569 - 2581