Particle Swarm Optimization for Resource Allocation in UAV Cooperative Control
Jose B. Cruz, Genshe Chen, Dongxu Li, Xu Wang · AIAA Guidance, Navigation, and Control Conference and Exhibit · 2004
Multiple Unmanned Aerospace Vehicle (UAV) resource allocation is one of the core steps to effectively exploit the capabilities of cooperative control of UAV teams. Although many multi -UAV resource allocation models can be found in the literature, relatively little has been said regarding soft weapon systems such as de coys and jammers, designed make the threat ineffective. In this paper, we formulate the resource allocation problem as an optimal assignment problem and present a new algorithm that is based on the principles of Particle Swarm Optimization (PSO). PSO follo ws a collaborative population based search, which models the social behavior of bird flocks and fish schools. PSO combines local search methods with global search, attempting to balance exploration and exploitation. We discuss the adaptation and implementa tion of the PSO search strategy to the resource allocation problem in the cooperative control of multiple UAVs. Simulation results indicate that the PSO based algorithm is a feasible approach for resource allocation problems in multiple UAV teams.