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Nonlinear estimation of the Bouc-Wen model with parameter boundaries: Application to seismic isolators

机译:具有参数边界的Bouc-Wen模型的非线性估计:在地震隔离器中的应用

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摘要

The Bouc-Wen model is one of the most widely used parametric models of hysteresis. The exactness of the Bouc-Wen model depends on the correctness of the model parameters that are subjected to bound constraints in accordance with their physical meaning. Constraints and nonlinearities of the model introduce a complexity for the parameter estimation. In this paper, a constrained unscented Kalman filter (CUKF) is proposed in order to identify the hysteresis model parameters in a robust and reliable way. The adopted parameter estimator has been compared with the well-known extended Kalman filter (EKF) that is often used for nonlinear system identification. The effectiveness of the proposed approach has been verified by numerical simulations and experimental tests. In particular, for the experimental verification of the CUKF, the Bouc-Wen model has been adopted to describe the hysteretic shear behaviour of a seismic isolator. The results show that the CUKF provides better parameter identification than the EKF also taking into account parameter boundaries. (C) 2019 Elsevier Ltd. All rights reserved.
机译:Bouc-Wen模型是最广泛使用的磁滞参数模型之一。 Bouc-Wen模型的准确性取决于模型参数的正确性,这些参数根据其物理含义受到约束。模型的约束和非线性引入了参数估计的复杂性。本文提出了一种约束无味卡尔曼滤波器(CUKF),以便以鲁棒和可靠的方式识别磁滞模型参数。已将采用的参数估计器与通常用于非线性系统识别的著名扩展卡尔曼滤波器(EKF)进行了比较。数值模拟和实验测试证明了该方法的有效性。特别是,对于CUKF的实验验证,已采用Bouc-Wen模型来描述隔震器的滞后剪切行为。结果表明,在考虑参数边界的情况下,CUKF比EKF提供更好的参数识别。 (C)2019 Elsevier Ltd.保留所有权利。

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