期刊
AEROSPACE SCIENCE AND TECHNOLOGY
卷 60, 期 -, 页码 58-67出版社
ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
DOI: 10.1016/j.ast.2016.10.029
关键词
Unsteady aerodynamic; Post stall maneuver; Biaxial coupled oscillation; Improved ELM; Cross validation
资金
- National Natural Science Foundation of China [61374032, 61573286]
- Aeronautical Science Foundation of China [20140753012]
This paper presents an innovative unsteady aerodynamic modeling method based on the improved Extreme Learning Machine (ELM), which is further successfully applied into the biaxial coupled oscillation during the post stall maneuver flight. The underlying data of pitch-roll and yaw-roll coupled oscillation for the aircraft, which simulate the post stall maneuver such as Herbst maneuver and barrel roll, are obtained by the wind tunnel test equipment and then separated as training samples and testing samples. To reduce the prediction error, the cross validation method is employed. And the parameters including the connect weights between the input layer and the hidden layer, the bias and the number of the neurons in the hidden layer are selected based on the testing samples. According to the verifying samples, the comparison is accomplished among the back-propagation neural network (BPNN) method, the enhanced incremental ELM (El-ELM) method and the improved ELM method. The simulation results demonstrate that the improved ELM method has characteristics of high precision, strong versatility and fast prediction in the unsteady aerodynamic modeling. (C) 2016 Elsevier Masson SAS. All rights reserved.
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