摘要
针对小型无人直升机小稳定、强耦合、非线性的特点,建立了小型无人直升机悬停状态下行动力学模型.设计了一种基于最小乘与自适应免疫遗传算法(LS-AIGA)的辨识算法,根据辨识实验的需要研制了机载微小型导航、制导与控制系统(MGNC).利用飞行实验数据,根据本文的辨识算法,对所建立模型中未知参数进行了辨识.最后对得到的模型进行了验证与分析,结果表明模型辨识数据与真实飞行实验数据匹配较好,所建立模型能够反映小型无人直升机动力学特性.
Aiming at the instability,strong coupling and nonlinearity of small-scale helicopter（SUH）,a flight dynamics model of SUH under hovering state is established.Then an identification algorithm is designed based on least squares and adaptive immune genetic algorithm（LS-AIGA）,and an airborne micro navigation,guidance and control system（MGNC） is developed for the needs of identification experiment.Then unknown parameters of the model are identified using flight test data according to the proposed identification algorithm.Finally,the established model is validated and analyzed,and the results show that the model identification data and the actual flight test data match well,and the established model can reflect the dynamics characteristics of the SUH.
出处
《机器人》
EI
CSCD
北大核心
2012年第1期72-77,共6页
Robot
基金
国家杰出青年科学基金资助项目(60825305)
国家自然科学基金资助重点项目(60736025)
国家自然科学基金资助项目(60905056)
关键词
无人直升机
飞行动力学模型
系统辨识
最小二乘
自适应免疫遗传算法
unmanned helicopter
flight dynamics model
system identification
least squares
adaptive immune genetic algorithm
