Research On Decision And Coordinated Control Method Of Multi-Type Unmanned Surface Vehicle Swarm

With the continuous development of unmanned surface vehicle(USV),it has been widely used in military and civil fields such as anti submarine,reconnaissance,environmental monitoring,and mapping.With the complexity and large-scale of ocean tasks,in order to improve the efficiency and success rate of operations and give full play to the advantages of USV swarm,multi-USV collaborative operations will become the new trend of ocean tasks in the future.For different task operation requirements,the USVs engaged in may have heterogeneity in ship type,etc.Multi-type USV swarm has stronger complementarity in maneuverability and task execution capability,can meet the requirements of multi-task operation on the basis of giving play to the advantages of swarm,and has redundant operation capability and stronger system fault tolerance.This thesis takes the multi-type USV swarm as the research object aiming at the typical tasks that the USVs need to complete in large-scale operation scenarios,and facing the processes of task allocation,path planning and coordinated control in practical applications.Focusing on the heterogeneity of the USV,the work is carried out through the research method of "numerical simulations+real experiments" and main research results are listed as follows:First,the heterogeneity of the USVs in terms of ship type,dynamic performance,and task execution ability is established,and the judgment condition for considering the USV heterogeneity are given.Based on the 3-DOF motion model and perturbation theory,a unified motion model suitable for multi-type USV swarm is established.Based on one model scheme,the motion characteristics of all USVs in the swarm can be fully expressed,which provides a theoretical basis for the coordinated control of multi-type USV swarm.Second,the heterogeneities of both USVs and tasks are considered in the process of task allocation.By establishing the fitness function that represents the USV heterogeneity in terms of endurance and task execution capability,the winning neuron selection mechanism of the Self-organizing Map(SOM)neural network method is improved,and the task allocation method of USV swarm based on the improved SOM is proposed.Aiming at the heterogeneity of tasks,the task treatment list(TTL)technology and the improved ant colony optimization(ACO)algorithm are introduced into the proposed SOM method.The simulation results show that,on the basis of the heterogeneity of each USV,the proposed task allocation method can effectively meet the task precedence constraints and achieve the goal of maximizing revenue.Third,aiming at the influence of differences of USV types on path planning,based on the Fast Marching Square(FMS)method,the matching degree of different planned paths to USVs is quantified by establishing a path evaluation function.An adaptive adjustable fast marching square(AAFMS)method is proposed,which can adjust the FMS potential field adaptively according to the navigation states of USVs and in combination with the International Regulations for Preventing Collisions at Sea(COLREGs).The simulation results show that the path planned based on the AAFMS method can effectively coordinate the differences in the ship type and dynamic performance of USVs in the swarm.Under the condition of meeting the navigation state constraints of each USV,it reduces the adverse impact of the FMS potential field on the path planning of USVs when it is applied to a large-scale USV swarm,and can meet the requirements of COLREGs for dynamic collision avoidance.The applicability of FMS method in the area of path planning for USV swarm is hence improved.Afterwards,the swarm is divided into different sub-swarms according to the heterogeneity of USV’s ship type,and the distributed swarm coordinated control method is established based on the null space based(NSB)behavior method.Furthermore,internal collision avoidance classification is established based on the maneuverability of USVs in each sub-swarm,which reduces the calculation complexity of the proposed NSB method.The idea of virtual leader is introduced to simplify the design dimension of NSB behavior space and to ensure the synchronous realization of coordinated control and path following of the USV swarm.Dynamic collision avoidance strategies for USVs in accordance with COLREGs are designed,and a coordinated control method for multi-type USVs based on the hybrid NSB behavior method is proposed.The simulation results show that this method can effectively and synchronously realize the swarm maintenance,path following,collision avoidance and dynamic collision avoidance for USVs.And for USVs with different dynamic performance,it can also achieve the coordinated control effect with a better motion consistency.Finally,the effectiveness and reliability of the proposed swarm control method are verified by simulations and real experiments.Aiming at the typical application scenario of USV swarm,the scalability of the swarm and the effect of the corresponding methods in the process of path planning,formation keeping,coordinated control,task execution,dynamic collision avoidance are verified through numerical simulations.By the construction of the experimental platform of USV swarm,the real experiments of coordinated control of two US Vs and three US Vs were carried out respectively,which realized the cooperative planning for a small USV swarm with different dynamic performance,and further verified the effectiveness of the proposed theoretical methods in practical environments.