Towards Coordination Control For Unmanned Aerial Vehicle Flocking Through Hierarchical Weighting Mechanisms

UAV swarm has unique advantages in flexibility,scalability,and other aspects,and it is increasingly widely used in various fields.Therefore,it is urgent to develop a simple and effective swarm cooperative control algorithm so that UAVs can cooperate and efficiently to complete specific tasks.However,under the constraints of limited interaction radius and communication bandwidth,the flocking control of the UAV swarm always faces great challenges,especially in an environment with obstacles.Creatures in nature have limited brain intelligence and behavior ability,but they can emerge from simple interactions with their neighbors to form high intelligent and coordinated biological swarms.Inspired by this,this thesis takes the rotorcraft UAV swarm as the research object,designs and implements a biological heuristic coordination control algorithm for path tracking tasks under complex environmental space and limited interaction conditions.The main work and innovations are summarized as follows:1)Aiming at the problem of the UAV swarm coordination control,a control framework under two inputs of task guidance and external threats is constructed,and a biologically heuristic coordination control strategy is designed.Considering the complex communication conditions and environmental obstacles,this thesis analyzes and models the path tracking problem then builds the overall and individual control framework.By referring to the coordinated movement mechanism of pigeons,this thesis introduces the "information UAV" and the hierarchical weighting mechanism to design the bio-inspired cooperative control strategy of the flock to ensure the sufficient influence of the critical information in the swarm.2)Based on the biologically inspired coordination control strategy and the Vicsek model,a hierarchical weighted Vicsek model is designed to improve the speed of the entire group converging to the desired direction of movement.According to the communication topology,the UAVs in the swarm are divided into several layers.At the same time,the weighting rules are designed to assign different weights to the UAVs of different layers,so as to effectively distinguish the influence of different layers of UAVs.3)Considering the influence of complex space obstacles and limited interactive conditions,an obstacle avoidance coordination control algorithm and a limited interactive fuzzy control algorithm are proposed to improve the practicability of the hierarchical weighted Vicsek model in a complex task environment.The obstacle avoidance coordination control algorithm realizes obstacle avoidance and UAV collision avoidance,thus ensuring the safety of UAV swarm.The limited interaction fuzzy control algorithm can adjust the interaction radius of the drone in real time according to the degree of confusion and the number of interactions of the UAV swarm,ensuring the coordinated control effect of the UAV.4)Based on the high-fidelity software-in-the-loop simulation experiment environment,the effectiveness of the coordination control method based on the layered weighting mechanism is verified.Based on the unmanned universal platform XTDrone,a software-in-the-loop simulation experiment environment was built,and the coordination control experiment of UAV clusters on a scale of 6 and 12 was carried out respectively.The experimental results lay the technical foundation for the migration of this work to the application of UAV swarm.