In order to solve the path planning problem of multiple unmanned aerial vehicles (UAVs) cooperative target tracking in complex environment, a model predictive control (MPC) and advanced adaptive chemical reaction optimization (AACRO) algorithm is proposed. Based on the target tracking model, the centralized MPC is used as the real-time control framework of the path planning problem, and five index cost functions are designed to optimize the tracking performance under various constraints, and the optimal tracking path of the UAV is obtained.In view of the complexity of the above multi-dimensional problem, a new intelligent algorithm is used to solve the MPC control strategy. The simulation results show that the scheme is effective and feasible, and has important application value for cooperative target tracking of unmanned aerial vehicle group.