摘要
It is crucial to develop an effective controller for the multi-UAV system to contribute to the frontier fields, such as the electronic warfare. To address the dilemma of the cooperative formation with the high dimensional data, a deep neural network(NN) controller is developed in this paper. Firstly, a deep NN model is used to tune parameters of PID controller online. Secondly, this paper introduces an improved deep NN model integrating the momentum to improve the performance of the classical NN model and satisfy the condition for the real time cooperative formation. Lastly, the cooperative formation task is achieved by extending the proposed cooperative controller with an improved NN to the complex multi-UAV system. The simulation result of multi-UAV formation demonstrates the effectiveness of the proposed method, which achieves a faster formation than competitors.
投稿的翻译标题 | A Formation Flight Method with an Improved Deep Neural Network for Multi-UAV System |
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源语言 | 繁体中文 |
页(从-至) | 295-302 |
页数 | 8 |
期刊 | Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University |
卷 | 38 |
期 | 2 |
DOI | |
出版状态 | 已出版 - 1 4月 2020 |
关键词
- Improved deep neural network
- Momentum
- Multi-UAV formation
- PID controller
- Simulation