Distributed Target State Estimation And Cooperative Tracking Of Multiple Unmanned Surface Vehicles

The ocean is related to national security and sustainable human development,and it is a blue territory for which all countries compete.At present,marine operations presents an important developed trend of unmanned,intelligent and network.Unmanned surface vehicles(USVs)are the important carriers to change the future operations.an intelligent ocean vehicle capable of performing a variety of ocean operations.Cooperative operation of USVs has been widely used in military and civilian fields due to the fact they can complete complex tasks that cannot be completed efficiently or cannot be completed by one USV.Cooperative motion control scenarios include coordinated trajectory tracking,coordinated path following,coordinated target enclosing,and coordinated target tracking.Cooperative target tracking control technology plays a prominent role in the detection,recognition,capture and tracking of noncooperative targets.Typical applications of the cooperative target tracking control include “bee colony” tracking,cooperative target strike,and oil spill capture at sea.It has become one of the hot research topics in recent years.This dissertation investigates the problem of cooperative one target and multiple targets estimation and tracking control for multi-USV.The main works of this dissertation are as follows:Firstly,this dissertation investigates the problem of the distributed target state estimation and cooperative tracking of multi-USV subject to the incomplete sensing information,the model parameters uncertainty,and the marine environment disturbance.A distributed hierarchical cooperative target estimation and tracking control stricture is proposed.At the communication level,a distributed extended state observer(ESO)based on unidirectional communication topology is designed.The speed and location of noncooperative target are estimated.At the control level,a reduced-order ESO requiring only relative distance is designed.It not only realizes the synchronous estimation of the unknown dynamic uncertainty,but also simplifies the structure of the observer.An anti-disturbance position tracking control law based on reduced-order ESO is designed.The anti-interference ability of the cooperative target tracking control system is improved.The input-to-state stability of the closed-loop system is analyzed via cascade theory.Besides,the tracking errors are uniformly ultimately bounded.Simulations verify the effectiveness of the proposed control method.Secondly,this dissertation addresses the problem of the distributed target state estimation and cooperative tracking of multi-USV subject to the constrained communication resources and the communication delay.An event-triggered hierarchical coordinated target estimation and tracking control structure is proposed.At the communication level,a time-delayed distributed event-triggered ESO is designed,and a delay upper bound that can guarantee the stability of the estimation system is obtained,which not only effectively reduces the network communication frequency,but also reveals the essential relationship between the delay upper bound and the communication topology.At the control level,based on the reduced-order ESO,an event-triggered position tracking control law is proposed,which can significantly reduce the number of actuator actions.Based on the stability analysis,it is proven that the closedloop system is input-to-state stable,and all error signals are uniformly ultimately bounded.Moreover,it is proved that Zeno behavior can be avoided.Simulation results verify the effectiveness of the proposed control method.Thirdly,this dissertation investigates the problem of the distributed target state estimation and cooperative tracking of multi-USV subject to the denial-of-service(Do S)attack.A hierarchical cooperative target estimation and tracking control structure based on the state predictor is proposed.At the communication level,a distributed edge-triggered ESO is designed based on a state predictor.It realizes the distributed observation of the speed and position of noncooperative target under the communication link blocking caused by Do S attacks and improves the security of the estimation system.Compared with the point-based event triggering mechanism,the triggering condition of the proposed method only depends on the relative information between nodes,rather than the sum of all the information between nodes and all their neighbors,which further reduces the waste of communication resources and reduces the amount of computation.At the control level,a fixed-time ESO and a fixed time kinetic control law are proposed such that the estimation errors and tracking errors can converge to zero in a fixed time.Based on the stability analysis,it is proven that error signals are bounded.Moreover,it is proved that Zeno behavior of the edge-based event-triggered can be avoided.Simulation results verify the effectiveness of the proposed control method.Fourthly,this dissertation addresses the problem of the distributed target state estimation and cooperative tracking of multi-USV subject to the stationary multi-obstacle constraints and moving multi-obstacle constraints.A hierarchical optimal safety cooperative multi-target estimation and control structure is proposed.At the communication level,a distributed containment ESO is designed to estimate the velocity and position of convex hull spanned by the multiple target states.At the guidance level,based on control barrier functions(CBFs),the neighbor USVs and the obstacle constraints are integrated into the optimized safe guidance law design,and a quadratic optimization problem is formulated.By using the designed optimized safe guidance law,the collisions between multiple USVs and between USVs and obstacles are avoided.In the control level,a model-free target tracking control law by using an adaptive ESO is presented for each follower USV to realize the cooperative tracking of the convex hull spanned by the multiple targets under completely unknown kinetic model parameters.Using the proposed communication-guidance-control structure,each level is independent and cooperative,and the influence of the parameters of USV and external parameters on the stability and robustness of the system is reduced.It is proven that the error signals in the closed-loop system are uniformly ultimately bounded,and the closed-loop multiple USVs system is guaranteed for input-to-state safety.Simulation results are elaborated to substantiate the effectiveness of the proposed control method.