New distributed model predictive control method for UAVs formation with communication anomalies

This article investigates the formation problem of unmanned aerial vehicles (UAVs) in presence of communication anomalies including delay and data loss. A formation controller based on distributed model predictive control (DMPC) is proposed for the three-dimensional (3D) kinematic model of UAV. According to the different roles of UAVs, asynchronous and synchronous communication methods are used for information interaction in leader-follower (LF) formation. In consideration of communication anomalies, the assumed prediction states are applied to maintain UAVs in the predefined formation, and the updated rules for the assumed states are designed. The formation cost functions are developed for the leader and follower, respectively. The terminal feedback controllers of leader and followers are designed by 3D error model and linear matrix inequality (LMI) to derive the assumed terminal state converging to the desired value in case of communication anomalies. Utilizing the assumed prediction states of the leader and follower in the presence of communication anomalies, the collision avoidance constraint and error constraint are built to ensure the safety and formation accuracy. It is proved that the tracking and formation errors of UAVs can converge to zero in abnormal communication. Finally, simulations are conducted to verify the effectiveness of the proposed method.