Autonomous flight control system for unmanned helicopter using neural networks
Autonomous flight control system for unmanned helicopter using neural networks
复制标题
使用神经网络的无人直升机自主飞行控制系统
DOI：
10.1109/sice.2002.1195255
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发表时间：
2002
期刊：
影响因子：
--
通讯作者：
K. Inoue
中科院分区：
文献类型：
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作者：
H. Nakanishi;H. Hashimoto;N. Hosokawa;A. Sato;K. Inoue
本文介绍了为无人机开发自主飞行控制系统的方法。本研究使用了雅马哈发动机株式会社生产的无人直升机“RMAX”。由于直升机的动力学是非线性的，开发飞行控制系统很困难。本文提出了一种通过训练神经网络来设计控制器的有效方法。将经过训练的神经网络与在线训练神经网络或自适应控制器一起使用，很容易补偿未建模的不良影响或目标与环境的突然变化，因此控制系统可以具有很高的可靠性。飞行实验结果表明了我们方法的有效性。
This paper describes methods to develop autonomous flight control systems for UAVs. The unmanned helicopter "RMAX" produced by YAMAHA Motor Co., LTD. is used in this study. It was difficult to develop flight control systems, because the dynamics of the helicopter is nonlinear. An efficient method to design controllers by training neural networks is proposed in this paper. It is easy to use trained neural network together with online training neural networks or adaptive controllers to compensate undesirable effects which are not modeled or sudden changes of the target and environment, therefore the control system can be highly reliable. Results of flight experiments are shown to demonstrate the effectiveness of our approach.