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This paper focuses on the real time intelligent navigation scheme for unmanned surface vehicle (USV) subject to collision avoidance regulations. The proposed approach is formulated as two segments: the real time guidance principle with COLREGS-compliant collision avoidance mechanism and the finite-time adaptive event-triggered control algorithm. The pointed improvement for the artificial potential field (APF) can guarantee USV possess the excellent avoidance function in accordance with COLREGS regulations. Especially, when the obstacle makes dangerous actions, the emergency obstacle avoidance operation (EOAO) is implemented according to the real time position of obstacles. Based on the proposed guidance principle, a finite-time robust neural control algorithm is developed by fusion of the finite-time stability theory and event-triggered mechanism. The intermittent computing and communication can effectively reduce the energy and resource consumption of the control system. Moreover, the finite-time adaptive controller design contributes to smaller computation load and facilitates the implementation of the algorithm in ocean engineering. The semi global finite-time uniformly boundedness (SGFTUB) of the closed-loop system is guaranteed through the Lyapunov theory. Finally, the numerical simulation and comparison experiment are illustrated to verify the guidance and control performance of the proposed algorithm. • This paper proposes a novel real-time intelligent navigation strategy subject to collision avoidance regulations is proposed. • Pointed improvement for APF can guarantee USV possess the excellent avoidance function with COLREGS regulations. • When other vehicle failed to make collision avoidance action, the EOAO mechanism will be implemented that uses relative position. • Finite-time adaptive controller contributes to smaller computation load. [ABSTRACT FROM AUTHOR]

This paper studies a time-varying formation control problem of a swarm of autonomous surface vehicles (ASVs) with prescribed constraints. Every ASV suffers from unavailable velocities, saturated inputs, internal uncertainties, and external disturbances. A distributed finite-time performance-prescribed time-varying formation control method is proposed for ASVs. Specifically, an adaptive fuzzy state observer (AFSO) is firstly proposed to recover the unavailable velocity by using saturated inputs and estimated disturbances from the fuzzy logic system. Secondly, a tunnel prescribed performance (TPP) function is designed to limit tracking errors with a concise form and smaller overshoot. At the kinematic level, with TPP-based error transformation, a C 1 finite-time time-varying guidance law is proposed by using the smooth switch functions and recovered velocities. Next, a finite-time command filter based on Levant differentiator is presented to smooth the guidance signals. At the kinetic level, a C 1 finite-time saturated control law is developed with the estimated velocities and disturbances. Then, it proves that tracking errors of the proposed closed-loop system converge into a small neighborhood around the equilibrium within finite time while evolving under TPP constraints regardless of saturated inputs. Finally, comparison results are provided to demonstrate the effectiveness of the proposed distributed finite-time performance-prescribed time-varying formation control method. • Distributed finite-time performance-prescribed formation control method is proposed for ASVs. • The TPP with a concise form is developed to achieve smaller overshoot in a positive manner. • An adaptive fuzzy state observer is designed to recover unavailable velocities. [ABSTRACT FROM AUTHOR]

This paper is concerned with a coordinated search and rescue problem of heterogeneous ocean vehicle cluster composed of autonomous surface vehicles (ASVs) and autonomous underwater vehicles (AUVs) subject to model uncertainties and ocean disturbances. Firstly, a three dimensions (3D) cross domain kinematic controller with auto-stop function at the rescue points is designed for the coordinated ASV-AUV system by using a line-of-sight guidance law. Secondly, an event-triggered based communication mechanism is constructed to ensure that the ASV-AUV system can broadcast information at its trigger moments except to the auto-stop points. Finally, an adaptive motion control law based on a low-frequency learning fuzzy predictor is designed, which is able to filter out the high-frequency components of uncertainties and disturbances. The stability of the closed-loop system is proven by employing input-to-state stability and cascade stability analysis. Simulation results and numerical analysis show the effectiveness of the proposed 3D heterogeneous cross domain coordinated path following controller with auto-stop function for marine search and rescue. • In contrast to the existing coordinated path following controllers which applicable to a two-dimensional or three-dimensional coordinated control in the same domain, a three-dimensional cross domain coordinated controller with auto-stop function applicable to sea surface and underwater scenarios are constructed. • In contrast to the existing communication that cannot stop during the whole control period, a predictor-based event-triggered communication mechanism is proposed such that the narrow network band could be effectively alleviated, and the communication will be suspended at the rescue points. • In contrast to the existing predictor design methods, a low-frequency learning fuzzy predictors are presented not only to filter out high-frequency components of non-linearities uncertainties and unmodeled random external disturbances, but also to achieve fast adaptation. [ABSTRACT FROM AUTHOR]

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]

This paper investigates an improved event-triggered robust adaptive control algorithm for the marine surface vehicle with the fault compensating mechanism. A dynamic event-triggered mechanism is designed with a concise form to reduce the updating frequencies of the system state. Different from the exiting results, the proposed algorithm can ensure that both the controller and the state transmitter are activated synchronously only at the triggering instants. That can ameliorate the communication obstruction in both the channels of sensor-to-controller and controller-to-actuator. To improve the fault-tolerant capability of the theoretical algorithm, gain-related adaptive parameters are derived to compensate for gain uncertainties and possible actuator faults. In addition, a compensating term via the robust neural damping technique is introduced to stabilize the unpredictable perturbation from the model uncertainties and the external disturbance. Through the Lyapunov criterion, the corresponding closed-loop system is with the semi-global uniformly ultimately bounded (SGUUB) stability. The simulation results are illustrated to verify the effectiveness of the algorithm. • An event-triggered robust adaptive fault-tolerant control algorithm is proposed for marine vehicles. • A concise dynamic event-triggered condition is designed to guarantee an effective tradeoff. • The communication burden can be largely reduced in both the channels of the sensor-to-controller and the controller-to-actuator. [ABSTRACT FROM AUTHOR]

This paper investigates a novel robust adaptive fault-tolerant control algorithm for the path-following activity of the unmanned surface vehicle (USV) via the multiplied event-triggered mechanism. An improved multiplied event-triggered condition is designed by employing the estimate model with a concise form. Thus, the burden-some problem is released, especially for the channel from sensors to the controller. Besides, two discrete adaptive parameters are constructed to stabilize the perturbation caused by the gain constraint and actuator faults. The model uncertainties and the practical disturbance are compensated by utilizing neural networks (NNs) approximation, in which the weight updating is reduced with the robust neural damping technique. With the direct Lyapunov theorem, the semi-global uniformly ultimately bounded (SGUUB) stability can be guaranteed for the closed-loop system. Finally, both the simulation and the physical vehicle-based experiments are illustrated to verify the effectiveness of the algorithm. • A robust fault-tolerant control algorithm is proposed for unmanned surface vehicle. • The adaptive parameters are updated online to compensate for unknown actuator faults. • An improved multiplied event-triggered condition is designed with a concise form. • It can evade the unnecessary information transmission of the onboard control network. [ABSTRACT FROM AUTHOR]

This note investigates an event-triggered robust adaptive control for path following of the unmanned robot sailboat (URS) by employing the proportional integral sliding mode manifold and the robust neural damping technique in presence of marine practice. The dominant assignment of this note can be summarized into three points: (1) The double-layer virtual guidance is developed to generate the reference signal for three navigation conditions (i.e., the upwind sailing, the downwind sailing and the crosswind sailing). That can enhance the navigating automatism of the URS while the tacking and the gybing. (2) The system uncertainties are approximated by the radial basis function neural networks (RBF-NNs). To further simplify the controller form, the robust neural damping technique has been introduced to evade the updated information of the neural weights. Furthermore, the input saturation of the closed-loop control system is tackled by constructing the auxiliary variable in the control design. (3) The communication burden in the channel from the controller to the actuator can be reduced for merits of the event-triggered rule. Besides, the system chattering, caused by the marine disturbances has also been reduced through the proportional integral sliding mode manifold and gain-related adaptive law. The tracking errors of the closed-loop control system will converge to a compact set, and all the signals satisfy the semi-global uniformly ultimately bounded (SGUUB) stability. Finally, the effectiveness and the robustness of the proposed algorithm have been demonstrated via the numerical simulations under the simulated marine environment. • An event-triggered robust adaptive control is proposed for unmanned robot sailboat. • The corresponding guidance is designed for upwind, crosswind and downwind conditions. • The input saturation is tackled by the auxiliary variable in the control design. • The proposed algorithm is with lower communication burden and no chattering action. [ABSTRACT FROM AUTHOR]