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This paper presents an adaptive event-triggered control algorithm for sail-assisted unmanned surface vehicle (USV) under nonlinear modified logic virtual ship (LVS) guidance, which addresses the issues of communication load and input saturation constraint. In guidance module, the reference signal generated by LVS guidance is further processed by nonlinear modification rules. That can effectively remove the abrupt phenomenon of actuators. In the control module, a robust adaptive control technique for sail-assisted USV is proposed by fusing adaptive compensation technology and hybrid threshold event-triggered. Unnecessary transmission is reduced between controller and actuator by constructing hybrid threshold event-triggered mechanism. Different from most existing event-triggered mechanism with fixed threshold parameters, threshold parameters in hybrid threshold event-triggered are dynamically adjusted according to the demands of the controller. Furthermore, the compensation effect of sail on the dynamic mechanism is considered. Adaptive parameters of rudder and propeller are constructed to improve the robustness of the closed-loop system. Finally, the theoretical stability of the proposed method is proved by Lyapunov stability theorem, and the control performance is evaluated by simulation platform, which verifies that the scheme has reliable tracking accuracy under time-varying disturbances. • The nonlinear modified LVS principle is proposed to improve sail acting performance. • The hybrid threshold parameter setting can obtain satisfactory resource efficiency. • It can be effectively released the coupling effect of sail force on power mechanism. • The triggered state variables are semi-globally uniform ultimate bounded stable. [ABSTRACT FROM AUTHOR]

A crucial and challenging issue in path following control of the autonomous surface vehicle (ASV) is input constraint and communication burden. In this paper, an intervened logic virtual ship (ILVS) guidance is developed to generate the reference signal, and further to tackle the input saturation constraint by employing the dynamic feedback evaluation rule. The main superiority of this design is to intervene the logic virtual ship (LVS) guidance principle to avoid the persistent large stabilization error. Associated with ILVS guidance framework, a robust adaptive neural event-triggered algorithm is proposed for the ASV by fusing the adaptive technique and the multiport event-triggered approach. The constrains of the model nonlinear term and the uncertain actuators gain are released by constructing online learning parameters. Furthermore, the channel resource from the sensor to the controller (SC) as well as the controller to the actuator (CA) is reduced for merits of the multiport event-triggered approach. The feedback error signals and the control inputs will be updated while the triggered condition is occurred. That also can eliminate the low frequency disturbance, caused by marine environment, to improve the robustness of the closed-loop system. Through the Lyapunov stability criterion, all state variables in the triggered point and triggered interval are achieved semi-global uniform ultimate bounded (SGUUB) stability. Finally, the control performance of the proposed method is evaluated on simulation platform, showing the satisfied tracking accuracy with the low transmission load. • The robust adaptive neural event-triggered control algorithm is proposed for the autonomous surface vehicle (ASV). • The developed intervened logic virtual ship (ILVS) guidance can generate the reference signal, and further to tackle the input saturation constraint. • The computing resource from the sensor to the controller, the transmission load from the controller to the actuator are reduced simultaneously. • All the state variables in the triggered point and triggered interval are achieved semi-global uniform ultimate bounded (SGUUB) stability. [ABSTRACT FROM AUTHOR]