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UCAV Path Planning by Fitness-Scaling Adaptive Chaotic Particle Swarm Optimization
Joint Authors
Zhang, Yudong
Wu, Le-nan
Wang, Shuihua
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-07-25
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Path planning plays an extremely important role in the design of UCAVs to accomplish the air combat task fleetly and reliably.
The planned path should ensure that UCAVs reach the destination along the optimal path with minimum probability of being found and minimal consumed fuel.
Traditional methods tend to find local best solutions due to the large search space.
In this paper, a Fitness-scaling Adaptive Chaotic Particle Swarm Optimization (FAC-PSO) approach was proposed as a fast and robust approach for the task of path planning of UCAVs.
The FAC-PSO employed the fitness-scaling method, the adaptive parameter mechanism, and the chaotic theory.
Experiments show that the FAC-PSO is more robust and costs less time than elite genetic algorithm with migration, simulated annealing, and chaotic artificial bee colony.
Moreover, the FAC-PSO performs well on the application of dynamic path planning when the threats cruise randomly and on the application of 3D path planning.
American Psychological Association (APA)
Zhang, Yudong& Wu, Le-nan& Wang, Shuihua. 2013. UCAV Path Planning by Fitness-Scaling Adaptive Chaotic Particle Swarm Optimization. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1032093
Modern Language Association (MLA)
Zhang, Yudong…[et al.]. UCAV Path Planning by Fitness-Scaling Adaptive Chaotic Particle Swarm Optimization. Mathematical Problems in Engineering No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-1032093
American Medical Association (AMA)
Zhang, Yudong& Wu, Le-nan& Wang, Shuihua. UCAV Path Planning by Fitness-Scaling Adaptive Chaotic Particle Swarm Optimization. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1032093
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1032093