Sliding mode control of multi-agent system with application to UAV air combat

Chang Liu, Shaoshan Sun, Chenggang Tao, Yingxin Shou, Bin Xu

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

This paper investigates the air combat mission between the multiple Unmanned Aerial Vehicle (UAV) and hostile multi-UAV. The multi-UAV air combat threat assessment model is firstly established to evaluate the situation of each drone in the combat scenario and then, the target allocation problem is formulated based on matrix game theory. To solve the target allocation problem, the modified Estimate of Distribution Algorithm (EDA) is proposed to search the best strategy. After the target allocation, the social behavioral based sliding mode control is finally constructed to realize the UAV swarm motion. The simulation experiment of multi-UAV air combat proves the validity of the algorithm.

Original languageEnglish
Article number107491
JournalComputers and Electrical Engineering
Volume96
DOIs
StatePublished - Dec 2021

Keywords

  • Air combat
  • Estimate of distribution algorithm
  • Game theory
  • Sliding mode control

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