Minimum time dynamic optimization using double-layer optimization algorithm

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 algor...

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Bibliographic Details
Published inProceedings of the 10th World Congress on Intelligent Control and Automation pp. 84 - 88
Main Authors Guo Xuan, Du Wenli, Qi Rongbin, Qian Feng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2012
Subjects
Chemical engineering
Chemicals
Computers
differential evolution algorithm
double-layer optimization algorithm
Dynamic programming
Educational institutions
Heuristic algorithms
minimum time dynamic optimization problem
Optimization
time range
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Summary: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.
ISBN:9781467313971
1467313971
DOI:10.1109/WCICA.2012.6357844