Formation Control of Multiple Unmanned Aerial Vehicles Based on Two-Layer Controller of Model Predictive Control Algorithm

This paper addresses the multiple unmanned aerial vehicle (UAV) formation motion control problem and presents a two-layer model predictive control (MPC) control algorithm. The global control framework consists of an outer distributed formation controller and an inner tube-based MPC optimization controller. The outer controller employs distributed model pre-dictive control (DMPC) to obtain the formation control vector. In the inner tube-based MPC controller, the state output of the upper controller is received as a control input and used as a reference state to solve for the optimal control vector. This optimal control vector is then combined with the control vector from the external DMPC controller to generate the final output. Compared to traditional MPC controllers, this two-layer MPC controller reduces computational complexity and effectively compensates for errors caused by external disturbances and model inaccuracies, improving convergence speed and reducing control errors in multi-UAV formation control. Simulation results demonstrate the effectiveness of the proposed algorithm in achieving formation control in the presence of disturbances.