Performance-based optimization of LQR for active mass damper using symbiotic organisms search

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Pei‐Ching Chen, Bryan J. Sugiarto, Kai-yi Chien
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引用次数: 5

Abstract

The linear-quadratic regulator (LQR) has been applied to structural vibration control for decades; however, selection of the weighting matrices of an LQR mostly depends on trial and error. In this study, a novel metaheuristic optimization method named as symbiotic organisms search (SOS) algorithm is applied to tuning LQR weighting matrices for active mass damper (AMD) control systems. A 10-story shear building with an active mass damper installed at the top is adopted as a benchmark for numerical simulation in order to realize the optimization performance considering three objective functions for mitigation of structural acceleration. Two common optimization methods including genetic algorithm (GA), and particle swarm optimization (PSO) are also applied to this benchmark for comparison purposes. Numerical simulation results indicate that SOS is superior to GA and PSO on searching the minimized solution of the three objective functions. Meanwhile, minimizing the square root of the sum of the squares of peak modal acceleration achieves the best control performance of structural acceleration among the three objective functions. In addition, force saturation is proposed and applied in the optimization process such that the control force level is close to the force capacity of AMD under specified earthquake intensity. Furthermore, the control performance of the optimized LQR is compared with that of the LQR designed by applying three common weighting selection methods when the 10-story building is subjected to various earthquake excitations. Simulation results demonstrate that the optimized LQR significantly outperforms the three LQRs on structural acceleration responses as expected and reduces story drift slightly better than the three LQRs. Finally, the performance-based optimized LQR is experimentally validated by conducting shake table testing in the laboratory. The experimental results and structural control performance are discussed and summarized thoroughly.
基于共生生物搜索的主动质量阻尼器LQR性能优化
线性二次型调节器(LQR)应用于结构振动控制已有几十年的历史;然而,LQR的加权矩阵的选择主要取决于试验和误差。在本研究中,一种新的元启发式优化方法被称为共生生物搜索(SOS)算法,用于调整主动质量阻尼器(AMD)控制系统的LQR加权矩阵。采用顶部安装主动质量阻尼器的10层剪切建筑作为数值模拟的基准,以实现考虑三个目标函数的优化性能,以减轻结构加速度。两种常见的优化方法,包括遗传算法(GA)和粒子群优化(PSO),也被应用于该基准以进行比较。数值模拟结果表明,SOS算法在搜索三个目标函数的最小化解方面优于GA和PSO算法。同时,最小化峰值模态加速度平方和的平方根,实现了三个目标函数中结构加速度的最佳控制性能。此外,提出了力饱和,并将其应用于优化过程中,使控制力水平接近AMD在特定地震烈度下的受力能力。此外,将优化后的LQR与应用三种常用加权选择方法设计的LQR在10层建筑受到各种地震激励时的控制性能进行了比较。仿真结果表明,优化后的LQR在结构加速度响应方面显著优于三种LQR,并比三种LQRs更好地降低了层间漂移。最后,通过实验室振动台测试,对基于性能的优化LQR进行了实验验证。对试验结果和结构控制性能进行了深入的讨论和总结。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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