文献类型：期刊文献

英文题名：Hybrid stochastic optimization method for optimal control problems of chemical processes

作者：Wu, Xiang Lei, Bangjun Zhang, Kanjian Cheng, Ming

第一作者：Wu, Xiang

通信作者：Wu, X[1]

机构：[1]Guizhou Normal Univ, Sch Math Sci, Guiyang 550001, Guizhou, Peoples R China;[2]Southeast Univ, Sch Elect Engn, Nanjing 210096, Jiangsu, Peoples R China;[3]Guizhou Inst Technol, Elect Engn Coll, Guiyang 550003, Guizhou, Peoples R China;[4]Southeast Univ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China;[5]Southeast Univ, Minist Educ, Key Lab Measurement & Control CSE, Nanjing 210096, Jiangsu, Peoples R China

第一机构：Guizhou Normal Univ, Sch Math Sci, Guiyang 550001, Guizhou, Peoples R China

通信机构：corresponding author), Guizhou Normal Univ, Sch Math Sci, Guiyang 550001, Guizhou, Peoples R China.

年份：2017

卷号：126

起止页码：297-310

外文期刊名：CHEMICAL ENGINEERING RESEARCH & DESIGN

收录：;EI(收录号：20174304306236);Scopus(收录号：2-s2.0-85031915522);WOS:【SCI-EXPANDED(收录号:WOS:000413387600027)】；

基金：The authors express their sincere gratitude to Professor E. Sorensen, the editor and the anonymous reviewers for their constructive comments in improving the presentation and quality of this manuscript. This work was supposed by the Chinese National Natural Science Foundation under Grant Nos. 61563011, 61703012, and 61374006, the Ph.D. research fund of Guizhou Normal University under Grant No. 119040514170, the project of Science and Technology Department of Guizhou province natural fund under Grant Nos. QiankeheJzi [2015]2070 and Qiankehejichu [2016]1064), and High level talent research project of Guizhou Institute of Technology under Grant No. XJGC20150405.

语种：英文

外文关键词：Chemical processes; Optimal control; Improved conjugate gradient algorithms; Stochastic search methods; Hybrid stochastic optimization approaches

摘要：In the paper, the optimal control problem of chemical process systems is considered. In general, it is very difficult to solve this problem analytically due to its nonlinear nature and the existence of control input constraints. To obtain the numerical solution, based on the time scaling transformation technology and the control parameterization method, the problem is transformed into a parameter optimization problem with some variable bounds, which can be efficiently solved using the improved conjugate gradient algorithm developed by us. However, in spite of the improved conjugate gradient algorithm is very efficient for local search, the solution obtained is usually a local extremum for non-convex optimal control problems. In order to escape from the local extremum, a novel stochastic search method is developed. A large number of numerical experiments show that the novel stochastic search method is excellent in exploration, while bad in exploitation. In order to improve the exploitation, we propose a hybrid stochastic optimization approach to solve the problem based on the novel stochastic search method and the improved conjugate gradient algorithm. Convergence results indicate that any global optimal solution of the approximate problem is also a global optimal solution of the original problem. Finally, four chemical process system optimal control problems illustrate that the hybrid numerical optimization algorithm proposed by us is low CPU time and obtains a better cost function value than the existing approaches. (C) 2017 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.