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Membrane structure active flatness control using genetic algorithm with online objective reweighting

机译:在线遗传加权的遗传算法膜结构主动平面度控制

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This paper presents experimental studies on active flatness control of a membrane structure using genetic algorithm (GA). Different from the previous algorithms with a single objective function, a genetic algorithm with online objective reweighting capability is proposed here. This genetic algorithm implements an objective function that re-weights its objective online and the objective function is the flatness plus tension. The goal of the reweighting genetic algorithm is to allow for a computationally efficient method by which membrane wrinkling can be reduced, while maintaining a consideration for control authority. Experiments are conducted on our membrane test facility with two implementations: a static mutation rate and an adaptive mutation rate. The experimental results show that the proposed genetic algorithm is able to converge on flatness while reducing the total amount of tension required.
机译:本文介绍了使用遗传算法(GA)控制膜结构的主动平面度的实验研究。与以前的具有单一目标函数的算法不同,本文提出了一种具有在线目标加权功能的遗传算法。该遗传算法实现了一个目标函数,该函数在线上对其目标进行加权,而目标函数是平坦度和张力。重加权遗传算法的目标是允许一种计算上有效的方法,通过该方法可以减少膜的起皱,同时保留对控制权限的考虑。在我们的膜测试设备上进行的实验有两种实现方式:静态突变率和自适应突变率。实验结果表明,提出的遗传算法能够收敛于平面度,同时减少所需的总张力。

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