Identification of nonlinear hysteretic systems has practical significance for the prediction of structural response. This paper develops a novel parameter identification method for nonlinear hysteretic systems. The Bouc–Wen model and its improved models are used to parametrically characterize the structural systems. Model parameters are identified using a given load‐displacement trajectory. The proposed method is developed under the framework of the sequence model optimization, which provides a broader search domain and needs fewer iterations. Firstly, a series of sensitivity analyses were conducted to investigate the effects of the Bouc–Wen parameters on the hysteresis behavior and to guide the identification process. Subsequently, based on the framework of the sequence model optimization, a novel strategy for identifying the model parameters of the nonlinear hysteresis system was proposed. Finally, the effectiveness and accuracy of the proposed algorithm were verified by the experimental data and numerical simulation results. The results indicate that the identified numerical model can accurately capture the strength and stiffness degradation and the pinching effect of the structural system. As a result, the predicted hysteretic trajectories are well agreed with the actual structural responses. The case studies demonstrate that the proposed method is sufficiently accurate and computationally efficient for the nonlinear hysteretic systems.

中文翻译：

---

使用基于序列模型的优化识别非线性滞后系统

非线性滞后系统的辨识对结构响应的预测具有实际意义。本文提出了一种新型的非线性滞后系统参数辨识方法。Bouc–Wen模型及其改进的模型用于参数化表征结构系统。使用给定的载荷-位移轨迹来识别模型参数。所提出的方法是在序列模型优化的框架下开发的，它提供了更广阔的搜索范围，并且需要更少的迭代。首先，进行了一系列敏感性分析，以研究Bouc–Wen参数对磁滞行为的影响并指导识别过程。随后，基于序列模型优化的框架，提出了一种新的非线性滞后系统模型参数辨识策略。最后，通过实验数据和数值仿真结果验证了该算法的有效性和准确性。结果表明，所识别的数值模型可以准确地捕获强度和刚度的下降以及结构系统的挤压效应。结果，预测的磁滞轨迹与实际的结构响应非常吻合。案例研究表明，所提出的方法对于非线性滞后系统具有足够的准确性和计算效率。结果表明，所识别的数值模型可以准确地捕获强度和刚度的下降以及结构系统的挤压效应。结果，预测的磁滞轨迹与实际的结构响应非常吻合。案例研究表明，所提出的方法对于非线性滞后系统具有足够的准确性和计算效率。结果表明，所识别的数值模型可以准确地捕获强度和刚度的退化以及结构系统的挤压效应。结果，预测的磁滞轨迹与实际的结构响应完全吻合。案例研究表明，所提出的方法对于非线性滞后系统具有足够的准确性和计算效率。