Multi-UAV tracking target in urban environments by model predictive control and improved whale optimizer

In this work, the method of Model Predictive Control (MPC) and Improved Whale Optimization Algorithm (IWOA) has been proposed to solve multiple unmanned aerial vehicles (UAVs) tracking a moving target in urban environment. The problem models are established, including the UAV model, target model, environment model and cost function model. Adopting MPC as a control framework for UAV target tracking, WOA is chosen as the solver of MPC. To further improve the optimized efficiency, the introduced strategies include bootstrap initialization strategy, double-difference variational strategy, adaptive weighting strategy and elite selection strategy. The compared experiments show the control method in this paper has better tracking performance and is a reliable technique for UAV tracking the moving target.