The NARX Model-Based System Identification on Nonlinear, Rotor-Bearing Systems
AbstractIn practice, it is usually difficult to obtain the physical model of nonlinear, rotor-bearing systems due to uncertain nonlinearities. In order to solve this issue to conduct the analysis and design of nonlinear, rotor-bearing systems, in this study, a data driven NARX (Nonlinear Auto-Regressive with exogenous inputs) model is identified. Due to the lack of the random input signal which is required in the identification of a system′s NARX model, for nonlinear, rotor-bearing systems, a new multi-harmonic input based model identification approach is introduced. Moreover, the identification results of NARX models on the nonlinear, rotor-bearing systems are validated under different conditions (such as: low speed, critical speed, and over critical speed), illustrating the applicability of the proposed approach. Finally, an experimental test is conducted to identify the NARX model of the nonlinear rotor test rig, showing that the NARX model can be used to reproduce the characteristics of the underlying system accurately, which provides a reliable model for dynamic analysis, control, and fault diagnosis of the nonlinear, rotor-bearing system. View Full-Text
Share & Cite This Article
Ma, Y.; Liu, H.; Zhu, Y.; Wang, F.; Luo, Z. The NARX Model-Based System Identification on Nonlinear, Rotor-Bearing Systems. Appl. Sci. 2017, 7, 911.
Ma Y, Liu H, Zhu Y, Wang F, Luo Z. The NARX Model-Based System Identification on Nonlinear, Rotor-Bearing Systems. Applied Sciences. 2017; 7(9):911.Chicago/Turabian Style
Ma, Ying; Liu, Haopeng; Zhu, Yunpeng; Wang, Fei; Luo, Zhong. 2017. "The NARX Model-Based System Identification on Nonlinear, Rotor-Bearing Systems." Appl. Sci. 7, no. 9: 911.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.