Minimum time dynamic optimization using double-layer optimization algorithm

Author

Guo Xuan ; Du Wenli ; Qi Rongbin ; Qian Feng

Author_Institution

Key Lab. of Adv. Control & Optimization for Chem. Processes, Shanghai, China

fYear

2012

fDate

6-8 July 2012

Firstpage

84

Lastpage

88

Abstract

A double-layer optimization algorithm (DLOA) was proposed to solve the minimum time dynamic optimization problem. The first step of DLOA was to discrete time region and control region. The inner optimization is to construct optimal control problem with free final states. Differential evolution algorithm is used to find the optimal solution in given terminal time, then the optimization results was compared with the threshold set. In the outer, DLOA calculated the time range of next iteration according to the inner calculation. When applied to typical minimum time dynamic optimization problem, DLOA demonstrated a competitive optimal searching ability and more accurate optimization results. DLOA could solve the optimization problem with local optimum and applied to models without gradient information.

Keywords

dynamic programming; evolutionary computation; iterative methods; optimal control; search problems; competitive optimal searching ability; control region; differential evolution algorithm; double-layer optimization algorithm; inner optimization; iteration; minimum time dynamic optimization; optimal control problem; terminal time; time region; Chemical engineering; Chemicals; Computers; Dynamic programming; Educational institutions; Heuristic algorithms; Optimization; differential evolution algorithm; double-layer optimization algorithm; minimum time dynamic optimization problem; time range;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2012 10th World Congress on

Conference_Location

Beijing

Print_ISBN

978-1-4673-1397-1

Type

conf

DOI

10.1109/WCICA.2012.6357844

Filename

6357844