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首页> 外文会议>AD-vol.69; American Society of Mechanical Engineers(ASME) International Mechanical Engineering Congress and Exposition; 20041113-19; Anaheim,CA(US) >MULTIOBJECTIVE GENETIC ALGORITHM APPROACH TO THE OPTIMIZATION OF A ROTATING FLEXIBLE ARM WITH ACLD PATCH
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MULTIOBJECTIVE GENETIC ALGORITHM APPROACH TO THE OPTIMIZATION OF A ROTATING FLEXIBLE ARM WITH ACLD PATCH

机译：多目标遗传算法在ACLD补丁旋转柔性臂优化中的应用

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摘要

This paper describes the use of multi-objective genetic algorithm (MOGA) to solve an integrated optimization problem of a rotating flexible arm with Active Constrained Layer Damping (ACLD) treatment. The arm is rotating in a horizontal plane with triangular velocity profiles. The ACLD patch is placed at the clamped end of the arm. The design objectives are to minimize the total treatment weight, the control voltage and the tip displacement of the arm, as well as to maximize the passive damping characteristic of the arm. Design variables include the control gains, the maximum angular velocity, the shear modulus of the viscoelastic layer, the thickness of the piezoelectric constraining and viscoelastic layers, and the length of the ACLD patch. The finite element method, in conjunction with the Golla-Hughes-McTavish (GHM) method, is employed to model the ACLD flexible arm to predict its dynamic behavior, in which the effects of centrifugal stiffening due to the rotation are taken into account. Reasonable Pareto solutions are successfully obtained. It is shown that MOGA is applicable to the present integrated optimization problem.
机译：本文介绍了多目标遗传算法（MOGA）的使用主动约束层阻尼（ACLD）处理解决旋转柔性臂的集成优化问题的方法。手臂在具有三角形速度分布的水平面中旋转。 ACLD贴片放置在手臂的夹紧端。设计目标是使总治疗重量，臂的控制电压和尖端位移最小化，以及使臂的被动阻尼特性最大化。设计变量包括控制增益，最大角速度，粘弹性层的剪切模量，压电约束层和粘弹性层的厚度以及ACLD贴片的长度。结合Golla-Hughes-McTavish（GHM）方法，采用有限元方法对ACLD挠性臂进行建模，以预测其动态行为，其中考虑了旋转引起的离心硬化的影响。成功获得了合理的帕累托解决方案。结果表明，MOGA适用于当前的集成优化问题。

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