Purpose

This paper aims to build an accurate mathematical model which is necessary for control design and attitude estimation of a miniature unmanned rotorcraft and its subsequent conversion to an autonomous vehicle.

Design/methodology/approach

Frequency-domain system identification of a small-size flybar-less remote controlled helicopter is carried out based on the input–output data collected from flight tests of the instrumented vehicle. A complete six degrees of freedom quasi-steady dynamic model is derived for hover and cruise flight conditions.

Findings

The veracity of the developed model is ascertained by comparing the predicted model responses to the actual responses from flight experiments and from statistical measures. Dynamic stability analysis of the vehicle is carried out using eigenvalues and eigenvectors. The identified model represents the vehicle dynamics very well in the frequency range of interest.

Research limitations/implications

The model needs to be augmented with additional terms to represent the high-frequency dynamics of the vehicle.

Practical implications

Control algorithms developed using the first principles model can be easily reconfigured using the identified model, because the model structure is not altered during identification.

Originality/value

This paper gives a practical solution for model identification and stability analysis of a small-scale flybar-less helicopter. The estimated model can be easily used in developing control algorithms.

中文翻译：

---

无翼旋翼飞机无人机系统识别

目的

本文旨在建立一个精确的数学模型，这对于微型无人旋翼飞机的控制设计和姿态估计以及随后的自动驾驶汽车转换是必不可少的。

设计/方法/方法

小型无翼遥控直升机的频域系统识别是基于从仪表车辆飞行测试中收集的输入输出数据进行的。针对悬停和巡航飞行条件，得出了一个完整的六自由度准稳态动力学模型。

发现

通过将预测的模型响应与飞行实验和统计测量的实际响应进行比较，可以确定所开发模型的准确性。使用特征值和特征向量进行车辆的动态稳定性分析。所识别的模型在感兴趣的频率范围内很好地表示了车辆动力学。

研究局限/意义

该模型需要增加其他项以表示车辆的高频动态。

实际影响

使用第一原理模型开发的控制算法可以使用识别出的模型轻松进行重新配置，因为在识别过程中模型结构不会改变。

创意/价值

本文为小型无副翼直升机的模型辨识和稳定性分析提供了一种实用的解决方案。估计的模型可轻松用于开发控制算法。