Application Analysis of Several Stochastic Optimal Algorithms in Adaptive Optics System Control

被引：0

作者：

Yang, Huizhen ^{[1
]}

Cai, Dongmei ^{[1
]}

Li, Xinyang ^{[1
]}

Jiang, Wenhan ^{[1
]}

机构：

[1] Chinese Acad Sci, Inst Opt & Elect, Chengdu 610209, Peoples R China

来源：

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23 | 2008年

关键词：

adaptive optics system; stochastic parallel gradient descent algorithm; simulated annealing; genetic algorithm; computer simulation;

D O I：

10.1109/WCICA.2008.4593628

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Optimizing the system performance metric directly is an important method for correcting wave-front distortions in adaptive optics(AO) systems. Appropriate stochastic parallel optimization control algorithm is the key to correcting distorted wave front successfully. Based on several stochastic parallel optimization control algorithms, an adaptive optics system with a 32-element deformable mirror was simulated. Genetic algorithm (GA), ALogrithm Of Pattern Extraction (Alopex), the single perturbation stochastic parallel gradient descent (SPGD), the double perturbation SPGD and simulated annealing (SA) were compared in convergence speed, correction capability and local maximum. The results are: because of low convergence speed, GA and Alopex are not suitable for the control of real-time AO system; and the double perturbation SPGD and SA hold significant promise for the control of AO system.

引用

页码：4391 / 4396

页数：6

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