Robust Adaptive Formation Control for Multi-Quadrotor Systems Under State Constraints

This paper presents a graph rigidity-based formation control law for multiple quadrotors, addressing parameter uncertainties and state constraints. A Barrier Lyapunov function and a saturation function are utilized to enforce constraints directly on the actual states rather than on state errors. Building upon the backstepping design methodology, formation control algorithms for multi-quadrotor systems are developed, consisting of a position control loop and an attitude control loop. In the position control loop, a formation controller based on rigidity graph theory is implemented, incorporating output and state constraints to effectively manage formation flight missions under various constrained conditions. Additionally, a Radial Basis Function (RBF) neural network is employed to compensate for system uncertainties, enhancing robustness and stability. In the attitude control loop, an attitude tracking controller is designed to ensure accurate attitude tracking. Finally, simulations are conducted to validate the effectiveness of the proposed control strategy.