Novel Control Vector Parameterization Method with Differential Evolution Algorithm and Its Application in Dynamic Optimization of Chemical Processes

孙帆; 钟伟民; 程辉; 钱锋

doi:10.1016/S1004-9541(13)60442-5

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Novel Control Vector Parameterization Method with Differential Evolution Algorithm and Its Application in Dynamic Optimization of Chemical Processes

过程系统工程与过程安全 | Updated：2026-01-06

- Novel Control Vector Parameterization Method with Differential Evolution Algorithm and Its Application in Dynamic Optimization of Chemical Processes
- Chinese Journal of Chemical Engineering Vol. 21, Issue 1, Pages: 64-711004-954160442-5(2013)
- Affiliations：
  
  2 Department of Automation, East China University of Science and Technology,Shanghai,China,200237
- Author bio：
- Funds：
- DOI：10.1016/S1004-9541(13)60442-5
  CLC：
- Published：2013
- Accepted：
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SUN Fan, ZHONG Weimin, CHENG Hui, QIAN Feng. Novel Control Vector Parameterization Method with Differential Evolution Algorithm and Its Application in Dynamic Optimization of Chemical Processes[J]. Chin.J.Chem.Eng., 2013, 21(1): 64-71.
DOI：

SUN Fan, ZHONG Weimin, CHENG Hui, QIAN Feng. Novel Control Vector Parameterization Method with Differential Evolution Algorithm and Its Application in Dynamic Optimization of Chemical Processes[J]. Chin.J.Chem.Eng., 2013, 21(1): 64-71. DOI： 10.1016/S1004-9541(13)60442-5.

摘要

Abstract

Two general approaches are adopted in solving dynamic optimization problems in chemical processes

namely

the analytical and numerical methods. The numerical method

which is based on heuristic algorithms

has been widely used. An approach that combines differential evolution (DE) algorithm and control vector parameterization (CVP) is proposed in this paper. In the proposed CVP

control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region

which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the proposed methods.

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