Fixed-interval smoothing of an aeroelastic airfoil model with cubic or free-play nonlinearity in incompressible flow
Fixed-interval smoothing, as one of the most important types of state estimation, has been concerned in many practical problems especially in the analysis of flight test data. However, the existing sequential filters and smoothers usually cannot deal with nonlinear or high-dimensional systems well....
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Published in | Acta mechanica Sinica Vol. 37; no. 7; pp. 1168 - 1182 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Beijing
The Chinese Society of Theoretical and Applied Mechanics; Institute of Mechanics, Chinese Academy of Sciences
01.07.2021
Springer Nature B.V |
Edition | English ed. |
Subjects | |
Online Access | Get full text |
ISSN | 0567-7718 1614-3116 |
DOI | 10.1007/s10409-021-01091-1 |
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Abstract | Fixed-interval smoothing, as one of the most important types of state estimation, has been concerned in many practical problems especially in the analysis of flight test data. However, the existing sequential filters and smoothers usually cannot deal with nonlinear or high-dimensional systems well. A state-of-the-art technique is employed in this study to explore the fixed-interval smoothing problem of a conceptual two-dimensional airfoil model in incompressible flow from noisy measurement data. Therein, the governing equations of the airfoil model are assumed to be known or only partially known. A single objective optimization problem is constructed with the classical Runge–Kutta scheme, and then estimations of the system states, the measurement noise and even the unknown parameters are obtained simultaneously through minimizing the objective function. Effectiveness and feasibility of the method are examined under several simulated measurement data corrupted by different measurement noises. All the obtained results indicate that the introduced algorithm is applicable for the airfoil model with cubic or free-play structural nonlinearity and leads to accurate state and parameter estimations. Besides, it is highly robust to Gaussian white and even more complex heavy-tailed measurement noises. It should be emphasized that the employed algorithm is still effective to high-dimensional nonlinear aeroelastic systems. |
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AbstractList | Fixed-interval smoothing, as one of the most important types of state estimation, has been concerned in many practical problems especially in the analysis of flight test data. However, the existing sequential filters and smoothers usually cannot deal with nonlinear or high-dimensional systems well. A state-of-the-art technique is employed in this study to explore the fixed-interval smoothing problem of a conceptual two-dimensional airfoil model in incompressible flow from noisy measurement data. Therein, the governing equations of the airfoil model are assumed to be known or only partially known. A single objective optimization problem is constructed with the classical Runge–Kutta scheme, and then estimations of the system states, the measurement noise and even the unknown parameters are obtained simultaneously through minimizing the objective function. Effectiveness and feasibility of the method are examined under several simulated measurement data corrupted by different measurement noises. All the obtained results indicate that the introduced algorithm is applicable for the airfoil model with cubic or free-play structural nonlinearity and leads to accurate state and parameter estimations. Besides, it is highly robust to Gaussian white and even more complex heavy-tailed measurement noises. It should be emphasized that the employed algorithm is still effective to high-dimensional nonlinear aeroelastic systems. |
Author | Kurths, Jürgen Xu, Yong Liu, Xiaochuan Li, Yongge Liu, Qi |
Author_xml | – sequence: 1 givenname: Qi surname: Liu fullname: Liu, Qi organization: School of Mathematics and Statistics, Northwestern Polytechnical University – sequence: 2 givenname: Yong surname: Xu fullname: Xu, Yong email: hsux3@nwpu.edu.cn organization: School of Mathematics and Statistics, Northwestern Polytechnical University, MIIT Key Laboratory of Dynamics and Control of Complex Systems, Northwestern Polytechnical University – sequence: 3 givenname: Yongge surname: Li fullname: Li, Yongge organization: School of Mathematics and Statistics, Northwestern Polytechnical University – sequence: 4 givenname: Jürgen surname: Kurths fullname: Kurths, Jürgen organization: Potsdam Institute for Climate Impact Research, Lobachevsky University of Nizhny Novgorod – sequence: 5 givenname: Xiaochuan surname: Liu fullname: Liu, Xiaochuan organization: AVIC Aircraft Strength Research Institute |
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SubjectTerms | Aeroelasticity Airfoils Algorithms Classical and Continuum Physics Computational Intelligence Engineering Engineering Fluid Dynamics Fluid flow Incompressible flow Mathematical models Noise measurement Nonlinear systems Nonlinearity Optimization Parameter estimation Research Paper Runge-Kutta method Smoothing State estimation System effectiveness Theoretical and Applied Mechanics Two dimensional models |
Title | Fixed-interval smoothing of an aeroelastic airfoil model with cubic or free-play nonlinearity in incompressible flow |
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