Discrete direct adaptive ELM controller for seismically excited non-linear base-isolated buildings

R. Subasri, A. Natarajan, S. Sundaram
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引用次数: 0

Abstract

Structures with fixed-base will produce high accelerations and inter-storey drifts and move laterally during earthquake. The presence of base isolation devices between ground and the structure, reduces the structural vibrations. To maintain the seismic response of structures within safety, service and comfort limits, the combination of base isolators and feedback controllers have been proposed in recent years. This paper proposes a discrete direct adaptive extreme learning machine (ELM) controller for the active control of non linear base isolated building with hysteretic isolation system. The controller is constructed based on a single hidden layer feed forward network and the parameters of the network are adapted using extreme learning machine (ELM) algorithm. In this work, different from the original ELM algorithm the output weights of the network are updated using Lyapunov stability approach, to guarantee the stability of the structure. The performance of the proposed controller is verified on a non-linear three dimensional benchmark base-isolated structure by exciting the structure with three earthquake samples. The result shows that the proposed controller is effective in reducing the seismic responses of the isolation members as well as the superstructure.
地震激励非线性隔震建筑的离散直接自适应ELM控制器
基础固定的结构在地震作用下会产生较大的加速度和层间漂移,并发生横向移动。在地面和结构之间的基础隔离装置的存在,减少了结构振动。为了保持结构在安全、使用和舒适范围内的地震反应,近年来提出了基础隔震器和反馈控制器的组合。提出了一种离散直接自适应极限学习机(ELM)控制器,用于非线性基础隔震建筑的滞后隔震系统的主动控制。该控制器基于单隐层前馈网络构造,并采用极限学习机(ELM)算法对网络参数进行自适应。与原有的ELM算法不同,本文采用Lyapunov稳定性方法更新网络的输出权值,保证了网络结构的稳定性。通过对一个非线性三维基准基础隔震结构进行三个地震样本的激励,验证了所提控制器的性能。结果表明,该控制器能有效地降低隔震构件和上部结构的地震反应。
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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