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Journal of System Simulation

Abstract

Abstract: In order to solve the dynamic multi-objective optimization problem with time correlation, this paper introduces the concept of time correlation feature and establishes the model of UAV timecorrelation dynamic multi-objective optimization problem moedl on the basis of UAV online track planning problem, and proposes a dynamic multi-objective double-layer optimization algorithm using adaptive predictive response mechanism and time-correlation optimization mechanism (DMOEA-APTC). The intensity of environmental change was judged according to the correlation of environmental change and different response mechanisms were used to quickly adapt to environmental change. In the optimization process, the least square method was used to learn the historical data to fit the future predicted value of the flight path, and the optimization mode of "only optimize the current" or "optimize the current and future at the same time" was adaptively selected according to the reliability of the prediction. The improved Chebyshev decomposition method was used to make the decision of the preferred flight path. The experimental results show that the proposed algorithm can reduce the flight duration and have higher survival probability in complex flight environments, improve the flight stability of the UAV, and deal with the online flight path planning more reasonably and effectively.

First Page

2086

Last Page

2099

CLC

TP273

Recommended Citation

Li Erchao, Zhang Shenghui. UAV Online Track Planning Based on DMOEA-APTC Algorithm[J]. Journal of System Simulation, 2024, 36(9): 2086-2099.

Corresponding Author

Zhang Shenghui

DOI

10.16182/j.issn1004731x.joss.23-0615

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