Event Driven Tracking Control For Unmanned Surface Vehicle With Multi-uncertainties

As a kind of small surface self-propelled vehicle,the Unmanned Surface Vessel(USV)is flexible and has extensive applications in civilian and military fields,such as the development and utilization of marine resources,maritime rescue,meteorological monitoring and reconnaissance.Tracking control is the basic control mode of USV control system,a good tracking control method is a powerful guarantee for USV to complete various tasks.While,the USV control system is a nonlinear system influenced by both environmental disturbance and system model uncertainty,and the velocity measurement value used in the control algorithm design is not easily obtained directly,it is of great theoretical significance and engineering value to study the output feedback tracking control algorithm,by considering the influence of multiple uncertainties based on the observer.Based on the mathematical model of USV,this paper studies the trajectory tracking control problem of USV with uncertainty and unmeasured speed,and put forward a robust output feedback tracking control algorithm,then,to reduce system energy consumption of control process,the event-driven output feedback tracking control algorithm is proposed.First,based on Lyapunov stability theory,the adaptive robust control is designed to deal with unknown disturbances.Taking account of unknown external disturbance and unmeasured speed,a recursive dynamic sliding mode output feedback control based on Extended State Observer(ESO)is presented.By designing a recursive sliding mode dynamic surface,the robustness of the control system can be ensured.Secondly,to deal with the trajectory tracking control problems of USV with multi-uncertainties,which are caused by model uncertainty and unknown external disturbance,a recursive sliding mode dynamic surface control method of nonlinear ship trajectory tracking output feedback is proposed based on a nonlinear gain observer.The RBFNN neural network is used to approximate the unknown part of model parameters,and the self-adaptive compensation term is designed to approximate estimated errors and disturbances,and simulation results are given.Finally,considering the limited onboard system energy,the event-driven control is proposed based on the above multi-uncertainty tracking control algorithms.Event-driven conditions are designed based on state variables,control instructions updates only when the event-driven conditions are satisfied.System stability is demonstrated based on lyapunov theory,no Zeno behavior is proved,and simulation results are given.