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首页> 外文期刊>International journal of computational methods >Optimal Sensors/Actuators Placement in Smart Structure Using Island Model Parallel Genetic Algorithm
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Optimal Sensors/Actuators Placement in Smart Structure Using Island Model Parallel Genetic Algorithm

机译：利用岛式平行遗传算法，最优传感器/执行器放置在智能结构中

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摘要

Determination of optimal placements of sensors/actuators in large structures is a difficult job as large number of possible combinations leads to a very high computational time and storage. Therefore, this kind of optimization problem demands a parallel implementation of the optimization schemes. Island model genetic algorithm (GA) being inherently parallel has been used for searching optimal placements of collocated sensors/actuators. Numerical simulations have been done for determination of optimal placements of collocated PZT sensors and actuators in smart fiber reinforced shell structures using island model parallel GA (IMPGA) in conjunction with electro-mechanical finite element analysis with an objective of maximizing the controllability index. It has been observed that the present IMPGA-based formulation (due to its migration scheme) not only makes it possible to determine optimal sensors/actuators locations for large structures but also leads to a better solution at a much reduced and achievable computational time. Results from scalability analysis also show that the efficacy of the present method of using IMPGA for determination of optimal sensors/actuators location based on FEA will be more pronounced when actually used for real life problems requiring large number of sensors and actuators.
机译：在大结构中的传感器/致动器的最佳放置的确定是困难的工作，大量可能的组合导致非常高的计算时间和存储。因此，这种优化问题要求并行实现优化方案。岛式模型遗传算法（GA）固有并行已经用于搜索并置传感器/执行器的最佳放置。已经完成了使用岛模型平行族（IMPGA）在智能纤维增强壳结构中的最佳放置的数值模拟，并使用岛模型平行族（IMPGA）结合电动机械有限元分析，其目的是最大化可控性指标的目的。已经观察到本发明的基于IMPA的配方（由于其迁移方案）不仅可以确定大型结构的最佳传感器/致动器位置，而且还可以在大大减少和可实现的计算时间内导致更好的解决方案。可伸缩性分析的结果还表明，当实际用于需要大量传感器和执行器的实际寿命问题时，使用IMPA的使用IMPA的使用方法的功效将更加明显。

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