提出一种基于自适应遗传算法的小型无人旋翼飞行器系统辨识方法.通过机载传感器设备,系统采集小型无人旋翼机的输入信号(舵机的控制信号)和输出信号(飞行器的姿态及速度等信息);经过数据预处理后,利用自适应遗传算法构建小型无人旋翼飞行器高精度动力学模型,并通过仿真和实验对模型的有效性进行验证.实验表明,基于本文提出的动态模型,小型无人旋翼机可以精确完成悬停和前飞任务.
A system identification method for the small unmanned aerial rotorcraft(SUAR) using adaptive genetic algorithm is proposed.Using the on-board sensor equipments,the system acquires the corresponding input information(control signals for digital servos) and output information(attitude and velocity information,etc.of the small unmanned aerial rotorcraft). After data pre-processing,a high precision dynamic model is constructed by using the adaptive genetic algorithm.And the effectiveness of the proposed dynamic model is verified by simulations and experiments.Experiments show that SUAR based on the proposed dynamic model can perform hovering and straight flight accurately.