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| Subspace Model Identification Method for Flight Dynamics of FixedWing Airplane |
| QI Xiaohui1,WANG Jianchen2
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| (1. Department of Unmanned Plane Engineering, Ordnance Engineering College, Shijiazhuang, 050003
China; 2. Northwestern Polytechnical University Military Representative Bureau, Xi’an, 710065 China) |
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Abstract Abstract： Due to notable advantages of simplicity and high efficiency, the subspace model identification (SMI) method becomes an attractive modeling approach for flight dynamics of the airplane system. However, because of the nonlinearity in the airplane system, SMI based model identification approaches which are designed for linear systems always generate some modeling errors. To deal with this problem, a novel twostage system identification approach for flight dynamics of the fixedwing airplane system was proposed. An instrumental variable aided closedloop SMI was first adopted to obtain the approximate linear model of the airplane dynamics. Then, an extended state observer (ESO) able to estimate the nonlinear dynamics of the airplane system was constructed using the obtained linear model. Based on the estimates by the ESO, a group of neural networks were trained to identify the decentralized model of the system nonlinearity. Finally, the nonlinear, six degreeoffreedom (6DOF) model of a B747 airplane was applied to system identification test, and the results obtained verify the effectiveness of the proposed approach.
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Received: 06 May 2015
Published: 28 April 2016
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