Trajectory Tracking And Formation Control Of Autonomous Surface Vessels Using Aperiod Sampling Sliding Mode Strategy

The application of autonomous surface vessels(ASVs)is more and more extensive.With the development of communication technology,the combination of network control and ASV control technology overcomes the shortcomings of traditional centralized control,such as the inconvenient installation and the difficult maintenance.How to reduce the transmission burden of the communication network with a nice system performance is an important research topic for the networked control systems.The aperiodic sampling mechanisms,such as quantization and event-triggered mechanisms,can reduce the frequency of signal transmission.This thesis considers the trajectory tracking and formation control of ASVs in the present of parameter uncertainties and external disturbances,trajectory tracking error constraints,actuator failures and input quantization.By using adaptive sliding mode control(SMC)technology,the event-triggered and quantization control laws are developed for the ASVs.The main results of this thesis are as follows:(1)For the event-triggered SMC for uncertain ASV system subject to unmeasured velocities and limited communication capacity,We consider the scenario where samplings of the system output and the control input are generated by two different event-triggered strategies.An event-triggered mechanism is incorporated in the sensor to decide when the position information is transmitted from the sensor to observer.The STA-based observer is developed to recover the unmeasured velocities by using event-triggered sampling of the position information.Besides,an SMC law is proposed and an input event-triggered mechanism is introduced to decide when the control signal is transmitted over the network to the actuator side.The stability for the overall closed-loop system is analyzed.It is proved that under the proposed output and input event-triggered strategies,there is no Zeno behavior exhibited.Examples are finally presented to illustrate the effectiveness of the proposed event-triggered STA-based observer and the event-triggered SMC scheme.(2)For the trajectory tracking problem of ASV system with constraint of tracking error,prescribed performance is used to ensure the transient performance of the system by using a transformed error.In case of the model uncertainties and external disturbances without the upper bound information,an adaptive SMC method based on barrier function is proposed.According to the values of sliding variables,we use a switching adaptive law which can make the sliding mode gain adjust adaptively without a priori information of parameter uncertainties and external disturbances.The uniform quantization mechanism is added to reduce the occupation of communication bandwidth.The stability of the whole closed-loop system is analyzed.Finally,the simulation results verify the effectiveness of control strategy.(3)For the formation control problem of ASVs among the leader and followers with prescribed performances,the model uncertainties,external disturbances and unknown actuator failures,a barrier function based adaptive sliding mode fault-tolerant formation control strategy is proposed.Using the concept of virtual trajectory,the formation system is divided into tracking subsystem and formation subsystem.The control laws of leaders and followers are designed respectively.The quantization mechanism is used for aperiodic sampling,which reduces the occupation of communication bandwidth.The stability of the whole closed-loop system is analyzed.And the simulation results verify the effectiveness of the proposed control strategy.