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Parameter identification for a nonlinear enzyme-catalytic dynamic system with time-delays

Author

Listed:
  • Jinlong Yuan
  • Lei Wang
  • Xu Zhang
  • Enmin Feng
  • Hongchao Yin
  • Zhilong Xiu

Abstract

In this paper, we consider a nonlinear enzyme-catalytic dynamical system with uncertain system parameters and state-delays for describing the process of batch culture. Some important properties of the time-delay system are discussed. Taking account of the difficulty in accurately measuring the concentrations of intracellular substances and the absence of equilibrium points for the time-delay system, we define quantitatively biological robustness of the intracellular substance concentrations for the entire process of batch culture to identify the uncertain system parameters and state-delays. Taking the defined biological robustness as a cost function, we establish an identification model subject to the time-delay system, continuous state inequality constraints and parameter constraints. By a penalty approach, this model can be converted into a sequence of nonlinear programming submodels. In consideration of both the difficulty in finding analytical solutions and the complexity of numerical solution to the nonlinear system, based on an improved simulated annealing, we develop a parallelized synchronous algorithm to solve these nonlinear programming submodels. An illustrative numerical example shows the appropriateness of the optimal system parameters and state-delays as well as the validity of the parallel algorithm. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Jinlong Yuan & Lei Wang & Xu Zhang & Enmin Feng & Hongchao Yin & Zhilong Xiu, 2015. "Parameter identification for a nonlinear enzyme-catalytic dynamic system with time-delays," Journal of Global Optimization, Springer, vol. 62(4), pages 791-810, August.
    • Handle: RePEc:spr:jglopt:v:62:y:2015:i:4:p:791-810
    DOI: 10.1007/s10898-014-0245-4
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    References listed on IDEAS

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    1. Ishibuchi, Hisao & Misaki, Shinta & Tanaka, Hideo, 1995. "Modified simulated annealing algorithms for the flow shop sequencing problem," European Journal of Operational Research, Elsevier, vol. 81(2), pages 388-398, March.
    2. U. Alon & M. G. Surette & N. Barkai & S. Leibler, 1999. "Robustness in bacterial chemotaxis," Nature, Nature, vol. 397(6715), pages 168-171, January.
    3. A. Ferreiro & J. García & J. López-Salas & C. Vázquez, 2013. "An efficient implementation of parallel simulated annealing algorithm in GPUs," Journal of Global Optimization, Springer, vol. 57(3), pages 863-890, November.
    4. Ahonen, H. & de Alvarenga, A.G. & Amaral, A.R.S., 2014. "Simulated annealing and tabu search approaches for the Corridor Allocation Problem," European Journal of Operational Research, Elsevier, vol. 232(1), pages 221-233.
    5. N. Barkai & S. Leibler, 1997. "Robustness in simple biochemical networks," Nature, Nature, vol. 387(6636), pages 913-917, June.
    6. Yuan, Jinlong & Zhu, Xi & Zhang, Xu & Yin, Hongchao & Feng, Enmin & Xiu, Zhilong, 2014. "Robust identification of enzymatic nonlinear dynamical systems for 1,3-propanediol transport mechanisms in microbial batch culture," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 150-163.
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