scholarly journals An Unmanned Helicopter Model Identification Method based on the Immune Particle Swarm Optimization Algorithm

Author(s):  
Tingting Yang ◽  
Aijun Li
2014 ◽  
Vol 1081 ◽  
pp. 358-362 ◽  
Author(s):  
Yu Xiang Zhang ◽  
Jian Hai Yang ◽  
Fu Hou Xu ◽  
Jia Zhao Chen

A damage identification method is proposed to identify the damage style and the damage parameters. By driving a pair of PZT patches out phase and in phase, the electric admittance of the PZT is obtained. The damage parameters are then identified from the changes of the admittance spectra caused by the appearance of damage. By comparing the identification result, the damage style can be determined and the damage parameters can be obtained. The middle basic particle swarm optimization algorithm is employed as a global search technique to back-calculate the damage. Experiments are carried out on beams. The results demonstrate that the proposed method is able to identify the damage style, and can effectively and reliably locate and quantify the damage in the beam.


2013 ◽  
Vol 347-350 ◽  
pp. 3890-3893 ◽  
Author(s):  
Ting Ting Yang ◽  
Ai Jun Li

An unmanned helicopter dynamic model identification method based on immune particle swarm optimization (PSO) algorithm is approved in this paper. In order to improve the search efficiency of PSO and avoid the premature convergence, the PSO algorithm is combined with the immune algorithm. The unmanned helicopter model parameters are coded as particle, the error of flight test and math simulation model is objective function, and the dynamic model of unmanned helicopter is identified. The simulation result shows that the method has high identification precision and can realistically reflect the dynamic characteristics.


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