Abstract
Aiming at the problem of UAV formation's obstacle avoidance and the consensus of position and velocity in a 3D obstacle environment, a novel distributed obstacle avoidance control algorithm for cooperative formation based on the improved artificial potential field (IAPF) and consensus theory is proposed in this paper. First, the particle model of the UAV and the dynamic model of the second-order system are established, and the topological structure of the communication network of the system is described with the knowledge of graph theory. Second, the attractive potential field function containing the coordination gains factor, the repulsive potential field function containing the influence factor of the repulsive force and the planning angle, and the potential field function between the UAVs containing the communication weight are defined. Then, the variables of position and velocity in the consensus protocol are improved by the reference vector of the formation center and the expected velocity, respectively, and a new formation obstacle avoidance control protocol is designed by combining the IAPF and the theory of consensus. Finally, the Lyapunov function is used to prove the stable convergence of the algorithm. The simulation results show that this method can not only prevent the UAV from colliding with each other while avoiding static and dynamic obstacles but also enable the UAV to quickly restore the expected formation and achieve the consensus of the relative distance, relative height, and velocity.
Highlights
In recent years, the cooperative control of multi-UAV systems has become a research hotspot in the field of aviation control [1,2,3]
Dai et al used the idea of segmentation to improve the attractive potential field function and the repulsive potential field function, introduced the rotation force and the potential field force between the UAVs, and corrected the state error of the UAV based on the consensus theory, and designed the obstacle avoidance control law of cooperative formation to achieve state consensus and trajectory planning [27]
The attractive potential field function containing the coordination gains factor is defined, and the influence factor of the repulsive force is introduced into the repulsive potential field function to prevent the UAV from falling into a local minimum and ensure that the UAV reaches the target point smoothly
Summary
The cooperative control of multi-UAV systems has become a research hotspot in the field of aviation control [1,2,3]. Belkacem K et al proposed a new distributed consensus algorithm based on the consensus theory for the cooperative control of the second-order multiUAV system to realize the formation avoidance and tracking control of UAVs [29] He XY et al designed a distributed adaptive consensus algorithm combined with the potential field method with distance constraints to enable the UAV to achieve tracking control in the anti-collision situation [30]. 3. A distributed cooperative formation obstacle avoidance control algorithm based on IAPF and consensus theory is proposed to achieve control objectives such as rapid obstacle avoidance, the consensus of the velocity of UAV, relative distance, and relative height between UAVs. The rest of the paper is organized as follows.
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