Review of ONR's Uninhabited Combat Air Vehicles Program

Uninhabited Combat Air Vehicles is a complicated global optimum problem. In this paper, according to the characteristics of Uninhabited Combat Air Vehicles, an improved bat algorithm was used to solve Uninhabited Combat Air Vehicles. The algorithm was experimented and the experimental results show that the improved algorithm to be successful in locating multiple solutions and better accuracy. Simulations and results indicate that the improved bat algorithm has better feasibility and validity for solving the multiple UCAV.

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A high-level “tasking” interface for uninhabited combat air vehicles

Proceedings of the 4th international conference on Intelligent user interfaces - IUI '99 ◽

10.1145/291080.291122 ◽

1999 ◽

Cited By ~ 1

Author(s):

Christopher A. Miller ◽

Michael Pelican ◽

Robert Goldman

Keyword(s):

High Level ◽

Uninhabited Combat Air Vehicles ◽

Air Vehicles

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Optimal Formation Reconfiguration Control of Multiple UCAVs Using Improved Firefly Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.389.828 ◽

2013 ◽

Vol 389 ◽

pp. 828-833 ◽

Cited By ~ 1

Author(s):

Yue Guang Li ◽

Jing Xing Fan

Keyword(s):

Local Search ◽

Firefly Algorithm ◽

Search Algorithm ◽

Global Optimum ◽

Experimental Results ◽

Location Update ◽

Formation Reconfiguration ◽

Improved Firefly Algorithm ◽

Uninhabited Combat Air Vehicles ◽

Air Vehicles

Optimal formation reconfiguration control of multiple is a complicated global optimum problem. In this paper, according to the characteristics of Uninhabited Combat Air Vehicles. A Novel Firefly Algorithm was used to solve Uninhabited Combat Air Vehicles, the redesign of the individual location update in the algorithm, and introduced a Levy flight to increase the population search domain. In addition, a local search algorithm is introduced to enhance the local search ability in this paper. the algorithm was experimented and the experimental results show that the new algorithm to be successful in locating multiple solutions and better accuracy. Series experimental results demonstrate the feasibility and effectiveness of the proposed method in solving the optimal formation reconfiguration control problem for multiple UCAV.

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