Trajectory Tracking And Cooperative Platooning Control Of Intelligent Connected Unmanned Container Transporter

As an essential part of modern waterborne transportation,ports play an more and more important role in the global trade and logistics system.China ranks first in the world in terms of 10,000-ton berth amount,cargo throughput,and container throughput.With the emergence of Ultra-Large Container Ship(ULCS),the efficiency of container loading,deporting and gathering has become a bottleneck,which is a choke point in the main artery of logistics.The newly-developing Unmanned Container Transporter(UCT),with the characteristics of intelligent connected and electric,provides a new solution for improving port operation efficiency and reducing dock labor cost.From a practical perspective,it is rewarding to investigate the cooperative control of the autonomous and intelligent UCT platoon for the automatic loading,unloading and transportation in the port area.These efforts will provide powerful support for improving the port traffic environment as well as raising the transporting efficiency.This thesis presents the trajectory tracking control and distributed cooperative control of intelligent connected UCT.The main works of this thesis are as follows:Firstly,this thesis studies the trajectory tracking control for omnidirectional UCT with uncertain model parameters and unknown external disturbances under the condition of narrow channels and safe speed.An adaptive dynamic surface controller(DSC)is proposed based on the radial basis function neural network(RBF-NN)and Barrier Lyapunov function(BLF).The RBF-NN is utilized to approximate the uncertainties and external disturbances in the system.And the BLF is used for the full-state constrained control of position and velocity,which ensures the safe operation of UCT.The stability analysis shows that the closed-loop system is semi-global uniformly bounded,and the effectiveness of the proposed full-state constrained adaptive dynamic surface controller is verified by simulation results and omnidirectional vehicle experiments.Next,this thesis studies the trajectory tracking control for Ackermann-based UCT with uncertain model parameters,skidding and slipping.At the kinematic level,constrained velocity control law is proposed to ensure unidirectional driving,which conforms to the traffic flow theory.At the dynamic level,the longitudinal velocity,lateral velocity and external disturbance are estimated by utilizing the extended state observer(ESO)and compensated in the control input when the measured velocity information is not available.The Input-to-State Stability(ISS)of the closed-loop system is analyzed by using the cascade theory,and the effectiveness of the proposed output-based controller is verified by simulation and experiment of Ackermann vehicle.Then,this thesis studies the cooperative control of network connected UCT subject to uncertain model parameters and unknown external disturbances.In-vehicle network is utilized to obtain the position information of neighbor UCT in the platoon,and a single parameterized path is used to guide the UCT platooning.At the kinematic level,a distributed guidance law and a path parameter updating law are respectively designed to calculate the desired velocity and heading angle.At the dynamics level,an ESO is used to estimate the states of the vehicle and its neighbors,and the longitudinal velocity and heading anti-disturbance control laws are designed and the disturbances are compensated.The closed-loop system is proven to be ISS via cascade theory,and all error signals are Uniformily Ultimately Bounded(UUB).Simulation results are given to demonstrate the effectiveness of the proposed distributed cooperative controller.The controller is subsequently applied to the maintenance vehicle on highway,and the performance of the controller is further verified by the experimental results.Finally,this thesis studies the distributed cooperative control for intelligent connected UCT platooning by using event-triggered mechanism.In the sensor-to-controller transmission channel for feedback information,an Event-Triggered ESO(ET-ESO)with inter-sample output predictor is proposed to recover the position-heading and velocity information as well as to estimate model uncertainties and unknown disturbances.The ESO estimation accuracy is improved by the proposed ET-ESO with fewer communication times and less resource consumption.In the controller-to-actuator channel for control information transmission,Zero-Order-Hold-based(ZOH)event-triggered mechanism(ETM)is introdued to reduce the action frequency of actuator.The distributed guidance law,path parameter updating law,velocity control law and heading control law are respectively designed at the kinematic level and dynamics level to realize the distributed cooperative control of UCT platooning.The input-to-state of the closed-loop system is analyzed via cascade theory and all tracking errors are proven to be UUB.Zeno behavior is excluded from the proposed ETMs by the analysis on minimum inter-event time.Simulation results substantiate the effectiveness of the proposed distributed event triggering controller for UCT platooning.