Robustness of nonlinear parameter identification in the presence of process noise using control-based continuation
Robustness of nonlinear parameter identification in the presence of process noise using control-based continuation
复制标题
DOI：
10.1007/s11071-021-06347-w
复制
发表时间：
2021-03-25
影响因子：
5.6
通讯作者：
Neild, Simon A.
中科院分区：
文献类型：
--
作者：
Beregi, Sandor;Barton, David A. W.;Neild, Simon A.
在这项研究中，我们认为实验获得的，周期性强迫响应的非线性结构中存在的过程噪声。基于控制的延续被用来测量稳定和不稳定的周期解，而不同程度的噪声被注入到系统中。使用这些数据，基于控制的连续算法的鲁棒性和其捕获无噪声系统响应的能力进行评估，通过识别相关的Duffing类模型的参数。我们表明，基于控制的延续提取系统信息更鲁棒，在存在高水平的噪声，比开环参数扫描，因此是一个有价值的工具，调查非线性结构。
In this study, we consider the experimentally obtained, periodically forced response of a nonlinear structure in the presence of process noise. Control-based continuation is used to measure both the stable and unstable periodic solutions, while different levels of noise are injected into the system. Using these data, the robustness of the control-based continuation algorithm and its ability to capture the noise-free system response are assessed by identifying the parameters of an associated Duffing-like model. We demonstrate that control-based continuation extracts system information more robustly, in the presence of a high level of noise, than open-loop parameter sweeps and so is a valuable tool for investigating nonlinear structures.