Online route planning based on mMarkov survival model and PSO algorithm
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V271.4

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    Aiming at the problem of route planning for aircraft under unknown condition, the online planning strategy is adopted to ensure that the aircraft can plan the future path in real time, and Markov survival model is introduced to obtain the survival probability of the aircraft, so as to evaluate the survival cost. Furthermore, missions, oil confusion, aircraft maneuverability are set as the objective function and constraints of PSO (Particle Swarm Optimization) algorithm. At the same time, self-adaptive weight strategy is presented to alleviate the contradiction between survival and missions. The simulation results show that the proposed online route planning strategy is feasible, and the self-adaptive weight also alleviates the contradiction between the survival and the mission. The application of Markov survival model in online route planning can indeed have more effective command at the survival cost and state probability of aircraft in each moment.

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Cite this article as: CUI Shu-Ting, ZHAO Cheng-Ping, ZHOU Xin-Zhi, NING Qian, YAN Hua. Online route planning based on mMarkov survival model and PSO algorithm [J]. J Sichuan Univ: Nat Sci Ed, 2018, 55: 501.

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History
  • Received:March 19,2017
  • Revised:March 19,2017
  • Adopted:July 19,2017
  • Online: June 06,2018
  • Published: