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首页> 外文期刊>Journal of Wind Engineering and Industrial Aerodynamics: The Journal of the International Association for Wind Engineering >Multi-level optimal design of buildings with active control under winds using genetic algorithms
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Multi-level optimal design of buildings with active control under winds using genetic algorithms

机译:基于遗传算法的风能主动控制建筑物的多级优化设计

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The goal of this paper is to study the complicated optimal design problem of integrating the number of actuators, the configuration of the actuators and the active control algorithms in buildings excited by strong wind force. To do this, the following sequential studies are carried out: (1) Two control algorithms, linear quadratic regulator (LQR) and acceleration feedback control algorithm, are analyzed and used as the control algorithms. (2) The characteristics of the optimal design problem are analyzed in detail by a simulation study. (3) A multi-level optimization model is proposed, and the formulation of sub-optimization problems in each level is presented. (4) To solve the multi-level optimization problem, a multi-level genetic algorithm (MLGA) is proposed. The properties and implementation of MLGA are given and analyzed in detail. Finally, the optimal design model and the corresponding solving algorithm are tested by numerical simulation. The results show that: (1) in the design of actively controlled structures subjected to strong wind excitation, the problem of considering the number of actuator,s the position of actuators and the control algorithm simultaneously is of a multi-level design optimization with the properties of non-linearity, discreteness and so on. (2) This kind of optimization problem should be described naturally be the multi-level design model. (3) The multi-level genetic algorithm can solve this complicated problem effectively. (4) The optimal locations of actuators depend on the control approaches.
机译:本文的目的是研究在强风力激励下的建筑物中集成执行机构数量,执行机构配置和主动控制算法的复杂优化设计问题。为此,进行了以下顺序研究:(1)分析了两种控制算法,线性二次调节器(LQR)和加速度反馈控制算法,并将其用作控制算法。 (2)通过仿真研究详细分析了最佳设计问题的特征。 (3)提出了一个多层次的优化模型,提出了每个层次的次优化问题的表述。 (4)为解决多级优化问题,提出了一种多级遗传算法(MLGA)。给出并详细分析了MLGA的特性和实现。最后,通过数值仿真对最优设计模型和相应的求解算法进行了测试。结果表明:(1)在强风激励下的主动控制结构设计中,同时考虑执行器个数,执行器位置和控制算法的问题是多级设计优化。非线性,离散等特性。 (2)这种优化问题应该自然地用多级设计模型来描述。 (3)多层遗传算法可以有效地解决这一复杂问题。 (4)执行器的最佳位置取决于控制方法。

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