Robust bi-objective optimal control of 1,3-propanediol microbial batch production process

被引:37
|
作者
Liu, Chongyang [1 ,3 ]
Gong, Zhaohua [1 ]
Lee, Heung Wing Joseph [2 ]
Teo, Kok Lay [3 ,4 ]
机构
[1] Shandong Inst Business & Technol, Sch Math & Informat Sci, Yantai 264005, Shandong, Peoples R China
[2] Hong Kong Polytech Univ, Dept Appl Math, Hung Hom, Kowloon, Hong Kong, Peoples R China
[3] Curtin Univ, Sch Elect Engn Comp & Math Sci, Perth, WA 6845, Australia
[4] Tianjin Univ Finance & Econ, Coordinated Innovat Ctr Computable Modeling Manag, Tianjin 300222, Peoples R China
基金
澳大利亚研究理事会;
关键词
Nonlinear time-delay system; Bi-objective optimal control; Normalized normal constraint; Numerical optimization; Batch process; NONLINEAR TIME-DELAY; NORMAL CONSTRAINT METHOD; PARAMETER-IDENTIFICATION; KLEBSIELLA-PNEUMONIAE; FERMENTATION; SYSTEM; OPTIMIZATION; PERFORMANCE; TRANSPORT; GLYCEROL;
D O I
10.1016/j.jprocont.2018.10.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper considers optimal control of glycerol producing 1,3-propanediol (1,3-PD) in batch process with uncertain time-delay and kinetic parameters. Based on a dynamic system with uncertain time-delay and kinetic parameters describing the batch process, we propose a robust bi-objective optimal control model, in which 1,3-PD productivity and glycerol consumption rate, and their semi-relative sensitivities with respect to the uncertain parameters are all involved in the vector objective. The control variables in this problem are the initial concentrations of biomass and glycerol and the terminal time of the process. Then, by introducing auxiliary time-delay systems and performing a time-scaling transformation, we transform the robust bi-objective optimal control problem into an equivalent bi-objective optimal control problem in standard form. Furthermore, we convert the equivalent optimal control problem into a sequence of solvable single-objective optimal control problems by using the normalized normal constraint method together with the constraint transcription technique. To solve each of the resulting optimal control problems, we develop a novel gradient-based solution method. Finally, numerical results are provided to verify the effectiveness of the proposed solution approach. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:170 / 182
页数:13
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