Abstract: To deal with the problem of cooperative area search for multiple unmanned aerial vehicles (UAVs),a decentralized optimization search method based on distributed model predictive control (DMPC) is presented in this article. First,based on the traditional search map model,a formal representation and system state space model of the multiple UAV cooperative search is established. Then,a centralized on-line optimization decision of the whole multiple UAV system is decomposed into the decentralized optimization of several single UAV subsystems under the framework of DMPC,and a Nash optimality and particle swarm optimization (PSO) based algorithm is implemented to the solution of the decentralized optimization. Simulation results demonstrate that the DMPC-based method can significantly reduce the size of multiple UAV optimization decision problems,and that it is a feasible approach for cooperative search.

Key words: unmanned aerial vehicles, cooperative area search, distributed model predictive control, particle swarm optimization, Nash optimality