Abstract The synthesis of structural health monitoring with vibration control is cost-effective and beneficial for developing smart structures. In the last decade, some synthetic algorithms have been proposed for combining system identification and vibration control. Among them, an approach has been developed recently for the synthesis of identification and vibration control under unknown excitation. However, these approaches are only suitable when structural measurement/observation equations contain the unknown excitations, which limits the application of this approach. In this paper, a general approach is proposed to tackle this limitation problem. A generalized extended Kalman filtering with unknown input (GEKF-UI) is proposed to circumvent the limitations of previous EKF-UI approaches. The proposed GEKF-UI can simultaneously identify structural system and unknown excitation when structural measurement/observation equations contain or do not contain the unknown excitations. Moreover, data fusion of measured acceleration and displacement responses is adopted to prohibit the drifts in the identified structural state and unknown excitations. Then, the identified structural state is synthesized in real time with the linear-quadratic-Gaussian (LQG) control strategy for optimal semi-active optimal control provided by magneto-rheological (MR) dampers. Some numerical examples for the synthesis of identification and vibration control of buildings subject to unknown external forces or unknown earthquake ground motion are adopted to verify the feasibilities of the proposed approach.

中文翻译：

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未知激励下建筑结构识别与振动控制的综合综合

摘要 结构健康监测与振动控制的综合具有成本效益，有利于开发智能结构。在过去的十年中，已经提出了一些综合算法来将系统识别和振动控制相结合。其中，最近开发了一种在未知激励下综合识别和振动控制的方法。然而，这些方法仅适用于结构测量/观测方程包含未知激励的情况，这限制了该方法的应用。在本文中，提出了一种通用方法来解决这个限制问题。提出了一种具有未知输入的广义扩展卡尔曼滤波（GEKF-UI）来规避先前 EKF-UI 方法的局限性。当结构测量/观测方程包含或不包含未知激励时，提出的 GEKF-UI 可以同时识别结构系统和未知激励。此外，采用测量加速度和位移响应的数据融合来抑制已识别结构状态和未知激励的漂移。然后，识别的结构状态与线性-二次-高斯 (LQG) 控制策略实时合成，以实现磁流变 (MR) 阻尼器提供的最佳半主动优化控制。通过一些数值算例，对受未知外力或未知地震动作用的建筑物进行综合识别和振动控制，以验证所提出方法的可行性。