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Synthesis Optimization of Piezo Driven Four Bar Mechanism Using Genetic Algorithm

机译:基于遗传算法的压电驱动四杆机构综合优化

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摘要

Over the past few years, there has been a growing demand to develop efficient precision mechanisms for fine moving applications. Therefore, several piezoelectric driven mechanisms have been proposed for such applications. In this work an optimal synthesis of a four-bar mechanism with three PEAs is proposed. Two evolutionary multi-objective Genetic Algorithms (GAS) are formulated and applied; A Genetic Algorithm Synthesis method (GAS) is first used to obtain a synthesis solution for the mechanism regardless of power consumption. Then another Genetic Algorithm Minimum Power Synthesis method (GAMPS) is used to obtain the synthesis solution of minimum power consumption. For that purpose, the study performs simulation investigation of the aforementioned algorithms for each point along sinusoidal and kidney shaped paths of motion. Results show capability of both methods in obtaining a synthesis solution. However, GAMPS outperformed GAS in terms of driving power consumption as it is minimized by 99% ratio.
机译:在过去的几年中,对开发用于精密移动应用的高效精密机构的需求不断增长。因此,已经针对这种应用提出了几种压电驱动机构。在这项工作中,提出了具有三个PEA的四杆机构的最佳综合方法。提出并应用了两种进化多目标遗传算法(GAS)。遗传算法综合方法(GAS)首先用于获得该机制的综合解决方案,而与功耗无关。然后使用另一种遗传算法最小功率综合方法(GAMPS)来获得最小功耗的综合解决方案。为此,本研究针对沿正弦和肾形运动路径的每个点对上述算法进行了仿真研究。结果显示了两种方法获得合成溶液的能力。但是,GAMPS在驱动功耗方面优于GAS,因为它以99%的比例最小化。

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