Multi-UAVs Target Tracking in Urban Environment Based on Distributed Model Predictive Control and Levy Flight-Salp Swarm Algorithm

To address the 3D target tracking problem in urban environment, a multi-unmanned aerial vehicles (UAVs) coordinated framework based on distributed model predictive control (DMPC) and a novel Levy flight-Salp Swarm Algorithm (LSSA) is proposed in this paper. First, the related models for target tracking are established, including the UAV kinematic model, urban obstacle environment, and their corresponding constraints. Second, the DMPC framework for multi-UAVs target tracking is proposed. Third, a recently proposed intelligent searching algorithm: SSA, is selected as the solver of the DMPC problem. To further improve the global searching performance of SSA, the Levy flight strategy is introduced to SSA, and the novel modified SSA is LSSA. Finally, a series of simulations are carried out to show the effectiveness of our proposed framework.