Adaptive Differential Evolution-based Receding Horizon Control Design for Multi-UAV Formation Reconfiguration

  • Boyang ZhangEmail author
  • Xiuxia Sun
  • Shuguang Liu
  • Xiongfeng Deng
Regular Papers


The complicated and constrained reconfiguration optimisation for unmanned aerial vehicles (UAVs) is a challenge, particularly when multi-mission requirements are taken into account. In this study, we evaluate the use of the adaptive differential evolution-based centralised receding horizon control approach to achieve the formation reconfiguration along a given formation group trajectory for multiple unmanned aerial vehicles in a three-dimensional (3D) environment. A rolling optimisation approach which combines the receding horizon control method with the adaptive differential evolution algorithm is proposed, where the receding horizon control method divides the global control problem into a series of local optimisations and each local optimisation problem is solved by an adaptive differential evolution algorithm. Furthermore, a novel quadratic reconfiguration cost function with the topology information of UAVs is presented, and the asymptotic convergence of the rolling optimisation is analysed. Finally, simulation examples are provided to illustrate the validity of the proposed control structure.


Adaptive differential evolution (DE) algorithm formation reconfiguration multiple unmanned aerial vehicles (UAVs) receding horizon control (RHC) rolling optimization 


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Copyright information

© ICROS, KIEE and Springer 2019

Authors and Affiliations

  1. 1.Department of Equipment Management and UAV EngineeringAir Force Engineering UniversityXi’anChina
  2. 2.Department of Electrical Engineering CollegeAnhui Polytechnic UniversityWuhuChina

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