| Citation: | WEI Zhenglei, ZHAO Hui, HUANG Hanqiao, et al. Dynamic UCAVs cooperative task allocation based on SAGWO algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(8): 1651-1664. doi: 10.13700/j.bh.1001-5965.2017.0589(in Chinese)
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Through analyzing unmanned combat aerial vechicle (UCAV) advantage probability and task joint threat and defining task time, the task allocation model for UCAVs with multi-constraint dynamic task allocation is built up, which takes target value damage, UCAV attrition and task expending time as the performance indexes, and the improved grey wolf optimization (GWO) algorithm is used to solve the model. Aimed at the flaw of early convergence from the original algorithm, the GWO algorithm is improved by proposing a self-adaptive adjustment strategy and a step-out local optimum strategy, using quadratic curve control method. According to the characteristics of UCAVs dynamic cooperative task allocation, target task sequence coding is designed to present the UCAVs dynamic task allocation method based on self-adaptive GWO (SAGWO) algorithm. Finally, the simulation results for static and dynamic task allocation show that the task allocation method based on SAGWO algorithm is valid, and compared with other algorithms, the optimizing process is rapid and accurate.
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