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Integrated fuzzy logic and genetic algorithms for multi-objective control of structures using MR dampers

机译:MR阻尼器用于结构多目标控制的集成模糊逻辑和遗传算法

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摘要

This study presents a design strategy based on genetic algorithms (GA) for semi-active fuzzy control of structures that have magneto theological (MR) dampers installed to prevent damage from severe dynamic loads such as earthquakes. The control objective is to minimize both the maximum displacement and acceleration responses of the structure. Interactive relationships between structural responses and input voltages of MR dampers are established by using a fuzzy controller. GA is employed as an adaptive method for design of the fuzzy controller, which is here known as a genetic adaptive fuzzy (GAF) controller. The multi-objectives are first converted to a fitness function that is used in standard genetic operations, i.e. selection, crossover, and mutation. The proposed approach generates an effective and reliable fuzzy logic control system by powerful searching and self-learning adaptive capabilities of GA. Numerical simulations for single and multiple damper cases are given to show the effectiveness and efficiency of the proposed intelligent control strategy. (c) 2006 Elsevier Ltd. All rights reserved.
机译:这项研究提出了一种基于遗传算法(GA)的半主动模糊控制结构设计策略,该结构已安装了磁流变(MR)阻尼器,以防止严重的动态载荷(例如地震)造成的损坏。控制目标是最小化结构的最大位移和加速度响应。通过使用模糊控制器来建立结构响应和MR阻尼器的输入电压之间的交互关系。 GA被用作设计模糊控制器的自适应方法,在此称为遗传自适应模糊(GAF)控制器。首先将多目标转换为适用于标准遗传操作(即选择,交叉和突变)的适应度函数。该方法通过强大的遗传算法搜索和自学习自适应能力,生成了有效,可靠的模糊逻辑控制系统。给出了单个和多个减振器情况的数值模拟,以显示所提出的智能控制策略的有效性和效率。 (c)2006 Elsevier Ltd.保留所有权利。

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