基于ACO-LEVY的小型无人直升机频域响应辨识方法  

Frequency domain response identification method for small unmanned helicopters based on ACO-LEVY

作　　者：刘鑫瑜 周健[1] 卢健[1] 王耿[2] LIU Xinyu;ZHOU Jian;LU Jian;WANG Geng(School of Electronics and Information,Xi’an Polytechnic University,Xi’an 710048,China;Unmanned System Research Institute,Northwestern Polytechnical University,Xi’an 710072,China)

机构地区：[1]西安工程大学电子信息学院,西安710048 [2]西北工业大学无人系统技术研究院,西安710072

出　　处：《兵器装备工程学报》2023年第4期245-251,274,共8页Journal of Ordnance Equipment Engineering

摘　　要：针对小型无人直升机在频域辨识中曲线拟合获得的模型预测精度较低的问题,提出了将蚁群优化算法和列维法(LEVY)相结合的一种新辨识方法。通过LEVY法获得初始模型结构,利用蚁群算法全局寻优特性的优点对初始模型结构中的参数进行优化,从而得到小型无人直升机传递函数模型。通过飞行数据验证表明,该方法能够较好地拟合频率响应曲线,提高辨识模型的预测精度,较为精确地反映小型无人直升机飞行动态特性。Aiming at the problem that the prediction accuracy of the model obtained by curve fitting in the frequency domain identification of small unmanned helicopters is low,this paper proposes a new identification method combining ant colony optimization algorithm and LEVY method.The initial model structure is obtained through the LEVY method,and the parameters in the initial model structure are optimized by using the advantages of the global optimization characteristic of the ant colony algorithm,thereby obtaining the transfer function model of the small unmanned helicopters.The flight data verification shows that the method can fit the frequency response curve well,improve prediction accuracy of the identification model,and more accurately reflect flight dynamic characteristics of the small unmanned helicopters.

关 键 词：小型无人直升机 频域辨识 频域曲线拟合 蚁群优化算法 LEVY法模型辨识 

分 类 号：V212.4[航空宇航科学与技术—航空宇航推进理论与工程]