Integrated Identification of the Nonlinear Autoregressive Models With Exogenous Inputs (NARX) for Engineering Systems Design
Integrated Identification of the Nonlinear Autoregressive Models With Exogenous Inputs (NARX) for Engineering Systems Design
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DOI：
10.1109/tcst.2022.3171130
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发表时间：
2022
影响因子：
4.8
通讯作者：
A. Kadochnikova;Yunpeng Zhu;Z. Lang;V. Kadirkamanathan
中科院分区：
文献类型：
--
作者：
A. Kadochnikova;Yunpeng Zhu;Z. Lang;V. Kadirkamanathan
本文提出了一种用于辨识具有外生输入的非线性自回归(AR)模型的新框架(NARX-M-FOR-D)，它表示工程系统的NARX，其中模型系数被显式地表示为可为系统设计调整的物理参数的函数。该框架致力于确定所有设计配置共享的NARX模型的公共结构，并确定将这些设计参数与NARX系数联系起来的非线性静态映射。利用扩展的正交化回归方法解决了共同结构的辨识问题，然后建立了一个联合回归问题来确定系统NARX系数与物理参数之间的显式关系。使用稀疏回归方法可以同时检测NARX模型的紧凑结构和设计参数图。简化后的结构提高了模型在设计参数空间的泛化能力，有利于辨识出的模型在系统设计中的应用。在基准模型和膨胀剂泡沫动态测试的实验数据上对框架的性能进行了评估。通过对识别模型的输出频率响应进行评估的实例，说明了在设计过程中如何使用所提出的框架来评估工程系统的动态特性。
This brief presents a new framework for the identification of nonlinear autoregressive (AR) models with exogenous inputs (NARX) model for design (NARX-M-for-D), which represents NARX of engineering systems where the model coefficients are represented explicitly as a function of the physical parameters that can be adjusted for the system design. The framework is concerned with identifying a common structure of the NARX model which is shared by all design configurations, and with identifying the nonlinear static maps that link these design parameters with NARX coefficients. The problem of the common structure identification is solved via extended forward orthogonal regression, after which a joint regression problem is formulated to determine the explicit relationships between NARX coefficients and physical parameters for the system. Using sparse regression methods allows simultaneous detection of a compact structure of the NARX model and design parameter maps. The reduced structure improves model generalization in design parameter space which is instrumental for the application of the identified model in the system design. The performance of the framework is evaluated on a benchmark model and on the experimental data from dynamic testing of auxetic foams. An example of evaluating the output frequency response from the identified model demonstrates how the proposed framework can be used to assess dynamical properties of engineered systems in the design process.