Formation Control Method For USVs Based On Back-Stepping Method And Adaptive Neural Network

Unmanned Surface Vehicles(USVs)with their advantages of small size,light weight,flexibility and low cost,have been widely used in marine environment monitoring,national defense security and marine resources exploration.Due to the narrow information perception range of single USV and its poor capacity of resisting disturbance,there are limitations to relying on single USV to cope with complex operating environment.Therefore,it is of great theoretical and practical significance to study the swarm formation control of USVs.This thesis mainly studies the formation control of USVs,and the contents are as follows:Firstly,the kinematics model of the USVs under three degree of freedom of surge,sway and yaw is established.Combined with the motion characteristics of USVs,the inertial coordinate system and the attached coordinate system were selected to describe the position information,linear velocity information and angular velocity information of USVs,and the kinematic model of USVs three degree of freedom was established by using the linear relationship between the two coordinate systems.At the same time,a dynamic model is established according to the internal structure of USVs,which lays a foundation for the study of formation control and collision avoidance of the USVs.Secondly,in view of the actual requirements of formation control and obstacle avoidance tasks of USVs,the leader-follower model is selected as the formation basis,the controller is designed by combining back-stepping method and its effectiveness is proved by Lyapunov function.In order to solve the convergence problem of the followers’ position error,a new guidance law function is designed.In addition,for the obstacles in the formation operating environment,the potential field function is designed based on the idea of artificial potential field method to make the USVs formation system avoid obstacles smoothly.The simulation results show that the formation control method proposed in this thesis can enable the USVs formation system to realize formation quickly,and can autonomously avoid collision when encountering obstacles and realize formation recovery in a short time,thus meeting the formation control and collision avoidance requirements.Finally,the USVs formation control problem of leader-follower method under the influence of external time-varying environment disturbances and actuator failures is considered in the complex and changeable sea environment,a new guidance law of fixed time convergence is proposed and a fixed time controller based on adaptive neural network is designed.A fixed-time observer is designed to estimate environmental disturbances and actuator failures,which are then compensated in the controller.The ultimate uniform convergence of all error signals is proved by the fixed time stability theory.In addition,the potential field function is designed to avoid collision between USVs in the formation system,the effectiveness of the proposed control method is verified by simulation experiments.In conclusion,the control strategy proposed in this thesis provides a new idea for the actual formation control of USVs.