Journal of Bionic Engineering

, Volume 5, Issue 4, pp 340–347 | Cite as

Optimal Formation Reconfiguration Control of Multiple UCAVs Using Improved Particle Swarm Optimization

  • Hai-bin DuanEmail author
  • Guan-jun Ma
  • De-lin Luo


Optimal formation reconfiguration control of multiple Uninhabited Combat Air Vehicles (UCAVs) is a complicated global optimum problem. Particle Swarm Optimization (PSO) is a population based stochastic optimization technique inspired by social behaviour of bird flocking or fish schooling. PSO can achieve better results in a faster, cheaper way compared with other bio-inspired computational methods, and there are few parameters to adjust in PSO. In this paper, we propose an improved PSO model for solving the optimal formation reconfiguration control problem for multiple UCAVs. Firstly, the Control Parameterization and Time Discretization (CPTD) method is designed in detail. Then, the mutation strategy and a special mutation-escape operator are adopted in the improved PSO model to make particles explore the search space more efficiently. The proposed strategy can produce a large speed value dynamically according to the variation of the speed, which makes the algorithm explore the local and global minima thoroughly at the same time. Series experimental results demonstrate the feasibility and effectiveness of the proposed method in solving the optimal formation reconfiguration control problem for multiple UCAVs.


uninhabited combat air vehicles particle swarm optimization control parameterization and time discretization optimal formation reconfiguration 


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Copyright information

© Jilin University 2008

Authors and Affiliations

  1. 1.School of Automation Science and Electrical EngineeringBeihang UniversityBeijingP. R. China
  2. 2.Provincial Key Laboratory for Information Processing TechnologySuzhou UniversitySuzhouP. R. China
  3. 3.Center for Systems and ControlXiamen UniversityXiamenP. R. China

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