Research On Coordination Control Of Multiple Underwater Vehicles For Ocean Exploration

Multiple Underwater Vehicles(usually represented by multiple Unmanned Underwater Vehicles,multi-UUVs)have advantages of high load capacity,high efficiency,and abundant system redundancy.However,coordination control relies on the ability of obtaining motion information of members rapidly and accurately,and the underwater communication environment and operating environment increase the difficulty of the control and research of multi-UUVs system.Based on the coordinated and stable operation is the prerequisite for the multi-UUVs formation to perform the marine task,multi-UUVs with high maneuverability are chosen as research objects,and the problem of coordination control is studied with the ocean exploration regarded as mission background.According to the coordination control problem at different stages of the exploration mission,the main problems,such as cooperative formation control,path following and formation transformation for real-time obstacle avoidance on conditions of limited communication and current disturbances,are studied and analyzed.In this paper,based on the system architecture of single UUV,considering of autonomy and coordination of UUVs in formation,the distributed control system architecture of multi-UUVs is built by using a coordination layer.To take the nonlinear coupling model of UUV as a control object,a coordination control system of multi-UUVs based on the method of accurate feedback linearization is proposed.The main content are shown as following:Firstly,due to the problems of the limited underwater acoustic communication bandwidth and the time delay,a method of coordination control of multi-UUVs based on the double independent communication topologies is proposed.According to the characteristics that each UUV can receive the position and velocity state information of different members at the same time with the topologies above,the stability of the formation system under the topology is verified by the consensus theory,and the two kinds of communication topologies are analyzed and compared,and then the equivalence relation between multi-UUVs' coordination control problem and consensus problem is established.On the other hand,in the view of time-varying delay in underwater communication,the Lyapunov-Razumikhin theory is used to derive the conditions which ensure the stable convergence of multi-UUVs during the process of formation building.On the basis of this,in the situation of unknown external disturbance and the absence of velocity state information,based on the extended state observer(ESO),the perturbation and velocity states of multi-UUVs can be obtained.Furthermore,the boundary condition of formation stable convergence under the communication condition can be derived.Secondly,due to the problems of the instability of underwater acoustic communication channels and the noise of ocean,a multi-UUVs' coordination control method based on double independent Markov switching topologies is proposed.According to the characteristics of the problems like the loss of vehicle caused by the interruption of communication in underwater communication,a switching topology based on Markov random process is built,which ensure that all the vehicles in the formation can communicate with others.In the view of time delays,the Lyapunov-Krasovskii function is used to analyze and obtain the sufficient condition for the stable convergence of multi-UUVs system on the condition of double independent Markov switching topologies with time-varying delay.On the basis of this,considering the nonlinear variation of hydrodynamic caused by underwater maneuvering,the additional nonlinear factor function satisfying the Bernoulli distribution is introduced and its influence on the stability of the vehicles system is analyzed.Due to the influence of ocean noise on the underwater acoustic communication channel,the Gaussian white noise is used to simulate ocean noise interference intensity in the underwater acoustic communication channels and channel effective ratio is used to present the validity of the motion state information of the member.Finally,the sufficient conditions for the stability of the aircraft formation system are obtained by using the noise stripping method.Thirdly,due to the obstacle avoidance problem in unknown environment,the paper proposes a method of autonomous obstacle avoidance of multi-UUVs with multiple active leaders based on coordinated identification method of unknown obstacle and improved artificial potential field method.According to the different tasks in the process of formation change,the leaders and followers are divided into separating level.In the level of active leaders,based on the characteristics of UUV's motion,an improved artificial potential field method is designed on the basis of coordinated obstacle identification method.The leaders can avoid obstacles in the situation of formation control,attraction of target point and repulsive force of obstacle without damaging the stability of the formation.In the level of followers,two kinds of autonomous leader-choice method based on the weighted communication chain and the relative position respectively are proposed which complete the formation process of autonomous grouping and following.Finally,due to the collision avoidance problem of multi-obstacles in unknown environment,a real-time autonomous obstacle avoidance local planning method for multi-UUVs based on real-time coordinated rapid extended random tree(RCRRT)algorithm is proposed.The real-time encounter probability map(REPM)is obtained by constantly updating the obstacle information,and the safety reference path point is generated by generation probability of the point by the RCRRT algorithm with the formation factors,stochastic factors and target factors.From the perspective of improving the validity of REPM,the information improving algorithm is designed by using the validity function and the balance function,and the optimal reference path is reconstructed from the neighborhoods of generated point by using the energy consumption function.