Design of a Multi-Constraint Formation Controller Based on Improved MPC and Consensus for Quadrotors

Abstract

The formation flight of quadrotor unmanned aerial vehicles (UAVs) is a complex multi-constraint process. When designing a formation controller, the dynamic model of the UAV itself has modeling errors and uncertainties. Model predictive control (MPC) is one of the best control methods for solving the constrained problem. First, a mathematical model of the quadrotor considering disturbance and uncertainty is established using the Lagrange–Euler formulation and is divided into a rotational subsystem (RS) and a translational subsystem (TS). Here, an improved MPC (IMPC) strategy based on an error model is introduced for the control of UAVs. The tracking errors caused by synthesis disturbance can be eliminated because of the integrator embedded in the augmented model. In addition, by modifying the parameters of the cost function, not only can the degree of stability of the closed-loop subsystem be specified, but also numerical problems in the MPC calculation can be improved. The simulation results demonstrate the stability of the designed controller in formation maintenance and its robustness to external disturbances and uncertainties.