Maneuvering Decision-making Method of UAV Based on Approximate Dynamic Programming

Changqiang HUANG; Kexin ZHAO; Bangjie HAN; Zhenglei WEI

doi:10.11999/JEIT180068

Volume 40 Issue 10

Sep. 2018

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Changqiang HUANG, Kexin ZHAO, Bangjie HAN, Zhenglei WEI. Maneuvering Decision-making Method of UAV Based on Approximate Dynamic Programming[J]. Journal of Electronics & Information Technology, 2018, 40(10): 2447-2452. doi: 10.11999/JEIT180068

Citation:

Changqiang HUANG, Kexin ZHAO, Bangjie HAN, Zhenglei WEI. Maneuvering Decision-making Method of UAV Based on Approximate Dynamic Programming[J]. Journal of Electronics & Information Technology, 2018, 40(10): 2447-2452. doi: 10.11999/JEIT180068

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Maneuvering Decision-making Method of UAV Based on Approximate Dynamic Programming

doi: 10.11999/JEIT180068

1.
College of Aeronautics of Engineering, Air Force University, Xi’an 710038, China
2.
Military Delegate Section of China People’s Liberation Army Air Force Stationed, Shijiazhuang 050002, China

Funds: The National Natural Science Foundation of China (61601505), The Aviation Science Foundation Project (20155196022)

Received Date: 2018-01-17
Rev Recd Date: 2018-06-20

Available Online: 2018-07-30

Publish Date: 2018-10-01

Abstract

Abstract

To solve the problem of dimension disaster when solving air combat maneuvering decision-making by dynamic programming, a swarm intelligence maneuvering decision-making method based on the approximate dynamic programming is proposed. Firstly, the Unmanned Aerial Vehicle (UAV) dynamic model and advantage functions of situation are established. On this basis, air combat process is divided into several stages according to dynamic programming thought. In order to reduce the search space, an Artificial Potential Field (APF) Guiding Ant Lion Optimizer (ALO) approximate optimal control amount is adopted in each programming stage. Finally, by comparing expert system, the experiment result indicates that the high dynamic and real-time air combat maneuvering decision can be solved by the proposed method effectively.
- Approximate dynamic programming,
- Unmanned Aerial Vehicle (UAV),
- Maneuvering decision-making,
- Swarm intelligence

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References(17)

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