Research on yaw crossing point optimization based on genetic algorithm
Yibo Li, Bin Feng, Yan Zhang · 2020
This paper proposes a yaw trajectory replanning method based on improved genetic algorithm, which improves the population quality by changing the confirmation method of crossover operator and mutation operator; by constructing fitness function and using the new constraints to search for new guidance Point method to achieve yaw track replanning of civil aircraft. Comparing the results obtained by the two, the improved genetic algorithm can effectively avoid the air threat zone while satisfying the Improve the efficiency of the solution. Finally, the simulation on the Matlab platform shows that the improved genetic algorithm accelerates the convergence speed, can plan a high-precision trajectory in a short time, and has good real-time performance. This method has good practicality in the civil aviation industry.