Momeni Zahrasadat, Bagchi Ashotush
Building Civil and Environmental Engineering Department, Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, Quebec, H3G 1M8, Canada.
Heliyon. 2023 Aug 24;9(9):e19381. doi: 10.1016/j.heliyon.2023.e19381. eCollection 2023 Sep.
Earthquakes can cause significant damage to constructed structures, leading engineers to design systems that effectively reduce damage and improve real-time vibration control. While base isolation is a commonly used passive method for seismic protection in highway structures, it has limitations such as a lack of immediate adaptation, constrained power dissipation capacity, and poor performance during earthquakes. To address the limitations of passive base isolation bearings, a hybrid control system that includes semi-active MR dampers is being introduced into isolated highway bridge structures. The aim is to enhance vibration reduction and improve overall performance. One of the major challenges in implementing this technology is developing appropriate control algorithms to handle the nonlinear behavior of semi-active devices. This paper proposes an adaptive data-driven control algorithm, informed by evolutionary game theory and a multi-objective optimization process, to optimize the distribution of voltage to semi-active MR dampers based on measurements of the damper's response to input signals. The algorithm is designed to provide optimal seismic protection. The performance of the replicator dynamics in the control system depends on three critical parameters: total population, which represents the total available resources or the sum of actuator forces; growth rate, which is the rate at which resources are distributed among control devices; and the fictitious fitness function, which regulates power consumption. Previous studies used sensitivity analysis to ascertain the best values for population size and growth rate, a time-consuming and unreliable process. This study aims to improve the performance of the system by solving a multi-objective problem. The proposed approach integrates a control algorithm with a multi-objective optimization algorithm, namely NSGA-II, to find Pareto optimal values for all parameters of the replicator dynamics. These parameters include total population, growth rate, and the fictitious function, with the aim of ensuring sustainability. By considering multiple objectives simultaneously, the proposed approach can provide a more comprehensive and effective solution for the bridge control problem. The effectiveness of this proposed approach is demonstrated through sample results Utilizing a case study centered around the Southern California Interstate 91/5 Overcrossing Highway Bridge, which is exposed to seismic activities.
地震会对建筑结构造成重大破坏,这促使工程师设计出能有效减少破坏并改善实时振动控制的系统。虽然基础隔震是公路结构中常用的被动地震保护方法,但它存在一些局限性,如缺乏即时适应性、能量耗散能力受限以及在地震期间性能不佳。为解决被动基础隔震支座的局限性,一种包含半主动磁流变阻尼器的混合控制系统正被引入到隔震公路桥梁结构中。目的是增强减振效果并改善整体性能。实施这项技术的主要挑战之一是开发合适的控制算法来处理半主动装置的非线性行为。本文提出一种基于进化博弈论和多目标优化过程的自适应数据驱动控制算法,以根据阻尼器对输入信号的响应测量结果来优化对半主动磁流变阻尼器的电压分配。该算法旨在提供最佳的地震保护。控制系统中复制动力学的性能取决于三个关键参数:总人口,它代表总可用资源或执行器力的总和;增长率,即资源在控制装置之间分配的速率;以及虚拟适应度函数,它调节功耗。先前的研究使用灵敏度分析来确定种群大小和增长率的最佳值,这是一个耗时且不可靠的过程。本研究旨在通过解决多目标问题来提高系统性能。所提出的方法将控制算法与多目标优化算法(即NSGA-II)相结合,以找到复制动力学所有参数的帕累托最优值。这些参数包括总人口、增长率和虚拟函数,目的是确保可持续性。通过同时考虑多个目标,所提出的方法可以为桥梁控制问题提供更全面有效的解决方案。利用以遭受地震活动的南加州91/5号州际公路跨线桥为中心的案例研究的样本结果,证明了所提出方法的有效性。