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Volume 41 Issue 11
Nov.  2015
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Journal of Beijing University of Aeronautics and Astronautics  > 2015  >  41(11): 1994-1999.
FU Li, XIE Fuhuai, MENG Guanglei, et al. An UAV air-combat decision expert system based on receding horizon control[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(11): 1994-1999. doi: 10.13700/j.bh.1001-5965.2014.0726(in Chinese)
Citation: FU Li, XIE Fuhuai, MENG Guanglei, et al. An UAV air-combat decision expert system based on receding horizon control[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(11): 1994-1999. doi: 10.13700/j.bh.1001-5965.2014.0726(in Chinese)
shu

An UAV air-combat decision expert system based on receding horizon control

doi: 10.13700/j.bh.1001-5965.2014.0726
  • 1.

    Faculty of Aerospace Engineering, Shenyang Aerospace University, Shenyang 110136, China

  • 2. School of Automation, Shenyang Aerospace University, Shenyang 110136, China

  • 3. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China

  • Received Date: 19 Nov 2014
  • Rev Recd Date: 13 Feb 2015
  • Publish Date: 20 Nov 2015
    Abstract
  • Aiming at the poor adaptability of expert system in air combat, a maneuvering decision algorithm based on the receding horizon control (RHC) method was proposed to improve the air combat maneuvering decision-making expert system. Firstly, the optimal control problem was systematically analyzed in the air combat maneuvering decision-making expert system. The system state equation, the index function and the control constraints of the maneuvering decision-making optimal control model were established. On this basis, according to the principle of the RHC method, the whole air combat process was divided into some sequential ones with the finite time horizon. In each time horizon, the optimal control model of the maneuvering decision-making expert system was solved to conduct air combat maneuvering decisions with initial state updated. The process was repeated until the air combat was over. The simulation result shows that, through solving the RHC optimal control model of the air combat maneuvering decision-making expert system, the unmanned aerial vehicle (UAV) can rapidly take effective maneuvering decisions in the case of expert system failure.

     

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