Research On Intermittent Coordinated Formation-Containment Control Of Multi-UUV System

With the rapid development of Unmanned Underwater Vehicle(UUV)and multi-agent technology,the issue of coordinated control of multi-UUV has received widespread attention.Compared with a single UUV,a multi-UUV system is capable of more complex tasks and working environments with higher task execution efficiency and better robustness.Containment control is a kind of formation control that does not require precise formation,which has a good application prospect in multiple multi-UUV systems.The formation control of multi-UUV systems faces many challenges.Firstly,the dynamic model of a UUV has the characteristics of underactuation,nonlinearity,strong coupling,uncertain parameters,etc.,and it is also disturbed by the external environment such as water flow during the movement.In the process of UUVs coordination,because of the usage of acoustic communication for UUVs’ information interaction in the underwater environment,time delay and packet loss will inevitably occur in the process of information transmission.The unfavorable factors above will greatly affect the stability of the system,so it is necessary to study these scenarios in the process of multi-UUV coordinated control.The main work of this paper is as follows:(1)For a multi-UUV system,in order to enable the leaders to track the given path and desired formation,and to enable the followers to enter the geometric figure formed by the leaders,a two-layer formation-containment control strategy will be designed.In the coordination layer,a distributed control protocol is designed for the leader UUVs,and a distributed containment control protocol is designed for the followers.In the control layer,because of the underactuation of UUV,the guidance law and terminal sliding mode controller are designed according to UUV’s kinematics and dynamics model.Finally,the formationcontainment control of the multi-UUV system is realized.(2)For the delay caused by UUV acoustic communication,an active predictive control strategy is adopted.UUV actively compensates for the time delay in the UUV communication process by predicting its own state in the future.A state prediction model was built using BP neural network.The existing UUV track data set was clustered for training respectively,so that UUVs can select different prediction models according to different current states.(3)For the problem of limited energy available during UUV’s underwater operations,in order to save energy during the communication process,which means reducing the communication frequency,a dynamic event trigger mechanism is adopted.To enable UUV to communicate with high-frequency during the formation process and with low-frequency to reduce the power when the formation has been stabilized and the formation is being maintained,so as to realize the efficient use of UUV communication information.