A weighted hybrid model for unsteady nonlinear aerodynamics

Zhao, Boxu; Luo, Guangsheng; Zhu, Jihong

doi:10.1109/icci-cc.2016.7862038

Cited by 2 publications

(2 citation statements)

References 16 publications

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“…The models combining physical mechanism perform better and are put to use more in practice. Various modelling methods with physical meaning have been suggested for unsteady aerodynamics, mainly based on step response model [3,4], state-space model [5,6], neural networks [7,8], and differential equation model [9].…”

Section: Introductionmentioning

confidence: 99%

Online identification of aerodynamics with fast time‐varying features using Kalman filter

Zhang

Zhu

2020

IET Control Theory & Appl

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This paper investigates the online identification method of the unsteady aerodynamics in the post-stall manoeuvres. The main unsteady features are hysteresis and fast time varying due to the complex flow structure at large angles of attack. When limited test data are available, the data-driven model cannot be identified accurately, especially in dealing with the fast time-varying features, so online identification is required. A constant acceleration model-based Kalman filter is constructed by taking into account the unsteady item in the aerodynamic model. Unlike the previous work which only uses the information of second-order moments of errors, the proposed method uses the maximum correntropy criterion. Simulation studies according to the wind tunnel test data show that the proposed method can effectively track the fast time-varying features and estimate the aerodynamic coefficients with high accuracy. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Introductionmentioning

confidence: 99%

Online identification of aerodynamics with fast time‐varying features using Kalman filter

Zhang

Zhu

2020

IET Control Theory & Appl

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“…The former is adopted more in practice, because the latter contains more uncertainties which makes the performance analysis complex and brings troubles to the design of control system. A series of unsteady aerodynamic modeling methods combining the knowledge of physical mechanism exist, including reduced frequency model [11], step response model [12], [13], state space model [14], [15], differential equation model [16], [17], etc.…”

Section: Introductionmentioning

confidence: 99%

LPV Modeling and Identification of Unsteady Aerodynamics for Fast Maneuvering Aircrafts

2019

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Fast maneuvers at large angles of attack are necessary for modern fighter aircrafts. The aerodynamic coefficients in this situation are unsteady, with the characteristics of hysteresis and fast timevarying. We propose an identification method based on the linear parameter varying (LPV) model. The model takes into account the hysteresis with respect to the angle of attack, and fast time varying with respect to the motion of post-stall maneuvers. By introducing the angular velocity as an exogenous variable, the model can guarantee the tracking ability of fast time-varying variations. We use the instrumental variable least squares (IVLS) algorithm to deal with the estimation problem. Finally, the experimental data obtained from maneuvers at large angles of attack from wind tunnel tests are used to validate the applicability and effectiveness of the proposed method. INDEX TERMS Instrumental variable least squares (IVLS) algorithm, large angle of attack, linear parameter varying (LPV) model, system identification, unsteady aerodynamics.

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A weighted hybrid model for unsteady nonlinear aerodynamics

Cited by 2 publications

References 16 publications

Online identification of aerodynamics with fast time‐varying features using Kalman filter

Online identification of aerodynamics with fast time‐varying features using Kalman filter

LPV Modeling and Identification of Unsteady Aerodynamics for Fast Maneuvering Aircrafts

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