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

机译:用于地震兴奋的非线性底座 - 隔离建筑物的离散直接自适应ELM控制器

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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.
机译:固定底座的结构将产生高加速度和层间漂移,并在地震期间横向移动。在地和结构之间存在基部隔离装置,降低了结构振动。为了保持安全,服务和舒适限制的结构的地震反应,近年来提出了基础隔离器和反馈控制器的组合。本文提出了一种离散的直接自适应极限学习机(ELM)控制器,用于滞后隔离系统的非线性底座隔离建筑物的主动控制。控制器基于单个隐藏层前馈网络构造,并使用极端学习机(ELM)算法来调整网络的参数。在这项工作中,与原始ELM算法不同,使用Lyapunov稳定方法更新网络的输出权重,以保证结构的稳定性。通过促进具有三个地震样品的结构,在非线性三维基准基准结构上验证了所提出的控制器的性能。结果表明,所提出的控制器有效地减少隔离构件的地震反应以及上层建筑。

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