Research And Design Of UAV’s Autonomous Formation Flight Control System

The UAV has the characteristics of low cost,good maneuverability,flexible operation and so on.It can replace human beings to carry out dangerous,harsh and cumbersome tasks.It has an extremely important role in modern warfare and has broad prospects in the civilian field.However,single UAV is often limited in their missions.The concept of multi-UAV cooperative formation flying has emerged.The latter has the advantages that single UAV do not have,and it has become a research hotspot in the field of intelligent control.This paper takes the small UAV formation system based on Leader-Follower structure as the main research object.By combining the computer collaborative work technology and the traditional control theory,this paper studies the multi-UAV formation maintenance,obstacle avoidance control algorithm and computer simulation technology.Firstly,this paper improves the construction of Voronoi diagrams based on application characteristics and environment for global flight environment modeling problems.The improved algorithm retains the advantages of the original method for adding,deleting,and modifying obstacles quickly and dynamically;instead of using the minimum coverage circle instead of the particle to model the obstacles,the basic information of the obstacles is restored,and the original information is overcome.The path generated by the algorithm may pass through the inside of the obstacle;the width of the path is checked to ensure the flight safety of the formation;the time complexity of the algorithm is the same as the original method,and the time performance is not lost due to the improvement of the construction mode.In this paper,the global optimal flight path planning for UAV formation is also carried out by A* heuristic search algorithm.The effectiveness of the improved Voronoi diagram in constructing flight environment is analyzed by design simulation experiments.Secondly,this paper proposes a calculation method for calculating the flight path of the Follower UAV based on the flight path of the Leader UAV in the formation.The algorithm calculation process is simple and relatively complete depicting the ideal flight path of each UAV in the formation.Aiming at the problem of the height component in the ground coordinate system and the long flight distance of the UAV flying outside the formation during the large-angle turn,the formation path optimization algorithm is proposed.The formation path optimization algorithm takes into account the turning radius problem of the UAV.Compared with the original path,the path optimized by the algorithm effectively reduces the flight distance of the outer UAV.The larger the angle,the more the distance is reduced.By designing simulation experiments,the results of the follower UAV flight path calculation method and the effectiveness of the formation path optimization algorithm on the path planning problem are analyzed and verified.Thirdly,this paper improves the design of the potential function of the artificial potential field method.The new potential function adjusts the flight speed of the Follower UAV according to the relative distance between the Follower UAV and the Leader UAV,and the formation system remains by realizes the relative distance in real time by dynamically measuring the relative distance.In this paper,the simulation experiment of formation order with obstacles is carried out on Matlab simulation tool Simulink,and the simulation results are analyzed.The experimental results show that the algorithm can effectively complete the formation maintenance task.Finally,this paper proposes an improved model based on the Leader-Follower structure UAV formation.When the leader UAV communication is disconnected or damaged,the new leader UAV can be selected to take over the task and pass the formation,and can be restored to the appropriate formation by formation reconstruction method.At the end of the article,the content and results of the research are summarized,and the future work is also forecasted.