基于改进遗传算法的动力伞气动参数辨识研究

Identification for Aerodynamic Coefficients of Powered Paraglider Based on Improved Genetic Algorithm

无人动力伞系统伞体部分由柔性冲压翼伞构成,翼伞的气动特性在整体系统中起重要作用。在无人动力伞建模过程中,由于柔性翼伞横侧向气动参数难以通过风洞试验测得,因此提出改进遗传算法来辨识得到翼伞横侧向气动参数。以标准遗传算法为基础,在交叉环节引入精英交叉来提高算法的收敛速度;在变异环节引入单代大概率变异操作,提高算法精度。通过对已知翼伞系统进行仿真,验证了改进遗传算法用于柔性翼伞气动参数辨识的效果。最后,在实际无人动力伞系统中,利用改进遗传算法获得其横侧向气动参数,通过与试验数据对比,说明通过辨识参数使系统具有良好的操纵性能。

Flexible stamping parafoil is part of the unmanned powered paraglider system. The aerodynamic char- acteristics of the parafoil play an important role in the system. In the modeling process, it is difficult to get lateral aerodynamic coefficients of parafoil by wind tunnel test. The paper proposed an improved genetic algorithm to identify lateral aerodynamic coefficients of parafoil. Based on standard genetic algorithm, a king - crossover strategy was in- troduced into cross process to improve the convergence rate. Big mutation occurred in some generation was introduced into variation process to improve the algorithm accuracy. Through simulating the known parafoil system, the effect of improved genetic algorithm was verified to identify the flexible parafoil aerodynamic coefficients. Finally, we used the improved genetic algorithm in the actual powered parachute system to obtain the lateral aerodynamic coefficients. By comparison with the experimental data, it was indicated that the recognition system contributed by characteristics i- dentification has good performance.