Abstract
Task scheduling is one of the core steps to effectively exploit the capabilities of cooperative control of multiple uninhabited combat aerial vehicles(UCAVs) team. The main function of multi-UCAV cooperative task scheduling is to allocate tasks which should be implemented by vehicles, and arrange the sequence of these tasks to be carried out for each vehicle simultaneously, while optimizing the team objective and satisfying various constrains of vehicles and tasks. By analyzing the characters of tasks and UCAVs, we presented a general mathematical model based on a combinatorial optimization. By defining a suitable particle structure, the Particle Swarm Optimization (PSO) algorithm was applied to solve this problem. Adaptive weight values and stochastic turbulence strategies were added to the algorithm. Simulation results indicate that the PSO algorithm proposed in this paper is a feasible and efficient approach for task scheduling in multi-UCAV cooperative control.
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Huo, X., Shen, L., Long, T. (2007). Particle Swarm Optimization for a Multi-UCAV Cooperative Task Scheduling. In: Szczuka, M.S., et al. Advances in Hybrid Information Technology. ICHIT 2006. Lecture Notes in Computer Science(), vol 4413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77368-9_30
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DOI: https://doi.org/10.1007/978-3-540-77368-9_30
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