Iterative learning-based formation control for multiple quadrotor unmanned aerial vehicles. (26th March 2020) - Zhao, Zhihui; Wang, Jing; Chen, Yangquan; Ju, Shuang
A double-layer formation control is proposed to solve the repeated tasks for multiple quadrotor unmanned aerial vehicle systems. The first layer aims at achieving a formation target in which the iterative learning control is designed based on relative distance with neighbor unmanned aerial vehicles and absolute distance with virtual leader unmanned aerial vehicle. The formation controller is responsible for keeping the formation shape and generating the desired flying trajectories for each drones. The second layer control aims at achieving a high-precision tracking to desired flying trajectories which are generated from the formation controller. A double closed-loop proportional–derivative strategy is designed to ensure the accuracy of trajectory tracking for each individual drone. Simulations for the circle formation mission of the multiple quadrotor unmanned aerial vehicle system are given to verify the efficiency of the proposed method.