Path planning based on model predictive control algorithm under moving threat

Jia Ren, Xiao Guang Gao, Yan Zhang

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Combining with the prediction of fast moving threat, the model predictive control(MPC) algorithm is adopted in the dynamic path planning for uninhabited air vehicles(UAVs). By using the converted measurement Kalman filter(CMKF) algorithm, the states of moving targets are predicted, and then the threats against UAV are evaluated, together with the length of path, to establish the cost function. The path planning is accomplished by obtaining a series of on-line control values which are figured out by minimizing the cost function in receding horizon. Finally, the application efficiency of MPC in path planning is validated by the simulation results.

Original languageEnglish
Pages (from-to)641-647
Number of pages7
JournalKongzhi Lilun Yu Yingyong/Control Theory and Applications
Volume27
Issue number5
StatePublished - May 2010

Keywords

  • CMKF
  • MPC
  • Path planning
  • UAV

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