Underactuated Surface Vessels Research Articles

Affine formation maneuver control of underactuated surface vessels: Guaranteed safety under moving obstacles in narrow channels

This research tackles the challenge of dynamic formation control and collision avoidance in underactuated surface vessels (USVs). Firstly, an affine transformation is employed to implement arbitrary configuration transformations within the multi-USV system. Secondly, by considering both distances and velocities between USVs and obstacles, a novel collision avoidance scheme is proposed based on conventional distance-based artificial potential field methods. This method, building on traditional distance-based artificial potential fields, offers a more precise assessment of collision risks, thereby notably shrinking the potential collision zones. Such refinement leads to reduced energy consumption and minimizes disruption to formation integrity. Thirdly, an anti-perturbation formation maneuver safety control scheme is introduced to achieve a time-varying target formation without collisions, ensuring that local position tracking errors remain bounded. The effectiveness of the proposed approaches is substantiated through comprehensive theoretical analysis and extensive numerical simulations, underscoring their practical applicability.

Event-triggered trajectory tracking control for USV with prescribed performance and time delay based on differential flatness

This paper presents a trajectory tracking control scheme for underactuated surface vessels (USVs) with input delay. Firstly, the underactuated surface vessel system is transformed into a fully actuated system using differential flatness theory. To estimate the unknown nonlinear terms introduced in the transformation process, a fuzzy neural network (FNN) is employed. Secondly, to conserve control resources and communication bandwidth, the controller of the system under prescribed performance is designed using the backstepping method. This method updates the controller according to an event-triggered condition that is designed using a Lyapunov function. Finally, theoretical proof and simulation experiments are conducted to demonstrate the convergence and effectiveness of the proposed method.

Self-tuning iterative learning control for an USV: Application to an autonomous berthing operation with an avoidance obstacle mechanism

This note focuses on the path planning and path-following control in the task of berthing for the underactuated surface vessel (USV), aiming to realize these functions that the accuracy of path-following can be preset and the smoother path planning based on the task of berthing. The proposed scheme is formulated as two components, i.e., the potential field virtual ship (PFVS) guidance part and the self-tuning iterative learning control (STILC) part. By utilizing one novel repulsive field applied around the obstacle and one corrected potential field, the PFVS guidance law is developed in the scheme to plan the reference path and program the real-time heading angle for the USV. The main superiorities of this design are that the guidance signal buffeting and target unreachable problem have been evaded in obstacle avoidance. In addition, the reference speed has been ingenious combined with the artificial potential field (APF). Furthermore, to improve the suitability of the closed-loop control system with ocean engineering, the iterative learning control (ILC) has been improved by introducing the input event-triggered mechanism. An STILC algorithm is designed for preset accuracy can achieve and reduce computing burden. In this algorithm, the number of iterations would self-turning based on the preset accurate. The computation burden of the proposed controller is reduce with the decreasing number of iterations. Through the Lyapunov analysis, we have exerted sufficient effort to ensure that all signals of the closed-loop control system are semi-globally uniformly ultimately bounded (SGUUB). The simulation experiments have been presented to verify the obstacle avoidance effectiveness and the burden-some superiority of the algorithm.

Practical Finite-Time Event-Triggered Control of Underactuated Surface Vessels in Presence of False Data Injection Attacks

Abstract The results of studies on a trajectory-tracking problem affected by false data injection attacks (FDIAs) and internal and external uncertainties are presented in this paper. In view of the FDIAs experienced by the system, we compensate for the serious navigation deviation caused by malicious attacks by designing an online approximator. Next, we study the internal and external uncertainties introduced by environmental factors, system parameter fluctuations, or sensor errors, and we design adaptive laws for these uncertainties to approximate their upper bounds. To further enhance the response velocity and stability of the system, we introduce finite-time technology to ensure that the unmanned underactuated surface vessels (USVs) reach the predetermined trajectory-tracking target within finite time. To further reduce the update frequency of the controller, we introduced event-triggered control (ETC) technology. This saves the system’s communication resources and optimizes the system. Through Lyapunov stability theory, a strict and complete stability analysis is provided for the control scheme. Finally, the effectiveness of the control scheme is verified using two sets of simulations.

Distributed finite-time bearing-based formation control for underactuated surface vessels with Levant differentiator

In this paper, a distributed bearing-based formation control scheme with finite-time convergency is proposed for multiple underactuated surface vessels (USVs). By virtue of the guide point-based model transformation method, the dimension of underactuated tracking error dynamics can be reduced from three to two. This allows us to convert the actuator model to a fully form that matches dimension-reduced tracking error dynamics. Further, to reduce the computation complexity, a finite-time recruited filter is designed according to first-order Levant differentiator. At meanwhile, auxiliary error compensation signals are introduced to address unknowns stemming from filter process and system dynamics. Since merely relative-distances and inner bearings are utilized in the proposed bearing-based formation approaches, the proposed control scheme provides a feasible solution to achieve formation control under body-fixed frame. Finally, theoretical analysis and numerical simulations are presented to demonstrate the efficacy.

Adaptive intelligent formation control for multiple underactuated surface vessels with prescribed performance

To control a leader-follower formation in underactuated surface vessels (USVs) with model uncertainty and external disturbances, a control strategy combining a fuzzy wavelet cerebellar model articulation controller (FWCMAC) and bidirectional fuzzy wavelet brain emotional learning controller (BFWBELC) is proposed in this paper to maintain connections between the USVs. Combined with the barrier Lyapunov function performance constraint method, a performance function is introduced as the boundary function of the formation error to ensure the transient and steady-state performance of the formation control system. FWCMAC is taken as the formation guidance controller, and the online learning law is derived using the gradient descent method. The BFWBELC is considered as the main controller, and the online learning rules are constructed by combining the bidirectional reward mechanism. The wavelet function is introduced to improve the processing ability of the controller for the stimulus signal. In addition, an adaptive compensator is proposed to handle the residual error of the adaptive intelligence controller with respect to the ideal controller. Based on Lyapunov stability theory, it is proven that all signals in the formation control system are ultimately bounded. The numerical simulation results demonstrate the effectiveness of the proposed formation control system.

Event-triggered adaptive command-filtered trajectory tracking control for underactuated surface vessels based on multivariate finite-time disturbance observer under actuator faults and input saturation

This paper is aiming at enabling the underactuated surface vessels (USVs) to complete the tracking task with high precision and fast convergence under the influence of unknown external interference, dynamic uncertainty, input saturation, limited communication resources, and actuator failure. Specifically, a trajectory tracking control scheme is designed using virtual control switching, robust self-adaptation, finite-time, event-triggered, and disturbance compensation techniques. The norm calculation is performed on the lateral and longitudinal errors of the underactuated USVs, and the virtual guidance direction of the system is obtained through virtual control conversion. The hyperbolic tangent function is introduced and combined with adaptive technology to compensate the dynamic uncertainty of the system. Through the multivariate finite-time disturbance observer (MFTDO), the unknown disturbance and the bias fault factor of the system are compensated. The tracking performance of the system is further improved using the finite-time technology and combined with the event-triggered technology to reduce the update frequency of the controller signal. Using Lyapunov stability theory, a detailed stability analysis is provided for the control scheme. Finally, the effectiveness of the control design scheme is verified by simulation.

Adaptive Optimal Tracking Control of an Underactuated Surface Vessel Using Actor-Critic Reinforcement Learning.

In this article, we present an adaptive reinforcement learning optimal tracking control (RLOTC) algorithm for an underactuated surface vessel subject to modeling uncertainties and time-varying external disturbances. By integrating backstepping technique with the optimized control design, we show that the desired optimal tracking performance of vessel control is guaranteed due to the fact that the virtual and actual control inputs are designed as optimized solutions of every subsystem. To enhance the robustness of vessel control systems, we employ neural network (NN) approximators to approximate uncertain vessel dynamics and present adaptive control technique to estimate the upper boundedness of external disturbances. Under the reinforcement learning framework, we construct actor-critic networks to solve the Hamilton-Jacobi-Bellman equations corresponding to subsystems of surface vessel to achieve the optimized control. The optimized control algorithm can synchronously train the adaptive parameters not only for actor-critic networks but also for NN approximators and adaptive control. By Lyapunov stability theorem, we show that the RLOTC algorithm can ensure the semiglobal uniform ultimate boundedness of the closed-loop systems. Compared with the existing reinforcement learning control results, the presented RLOTC algorithm can compensate for uncertain vessel dynamics and unknown disturbances, and obtain the optimized control performance by considering optimization in every backstepping design. Simulation studies on an underactuated surface vessel are given to illustrate the effectiveness of the RLOTC algorithm.

A Theoretical Analysis of the Velocity Obstacle Method for Nonholonomic Vehicles and Underactuated Surface Vessels

A Theoretical Analysis of the Velocity Obstacle Method for Nonholonomic Vehicles and Underactuated Surface Vessels

Underactuated surface vessels trajectory tracking control based on concise finite-time disturbance observer under False Data Injection Attacks

Underactuated surface vessels trajectory tracking control based on concise finite-time disturbance observer under False Data Injection Attacks

Saturation-Tolerant Adaptive Fixed-Time Control of Underactuated Surface Vessel With Improved Given Performances

Saturation-Tolerant Adaptive Fixed-Time Control of Underactuated Surface Vessel With Improved Given Performances

LPVS guidance and adaptive event-triggered control for an underactuated surface vessel with the prevention of obstacle’s vicious maneuvering

This paper investigates the adaptive neural event-triggered control for an underactuated surface vessel (USV), considering constraints of the obstacle’s vicious maneuvering and the limited communication channel. In the algorithm, a novel logical phantom virtual ship (LPVS) guidance principle is developed to generate the global path following reference and the obstacle avoidance order in the simulation results, where the corresponding operation comply to the suggestion in international regulations for prevention collision at sea (COLREGs). The improved design of velocity obstacle (VO) method can guarantee its predictive capability to prevent the obstacle’s vicious maneuvering. As for the control module, the adaptive event-triggered control algorithm is proposed by employing the robust neural damping technique and the input event-triggered mechanism. And the derived adaptive law can effectively solve perturbations from the gain uncertainty and the external disturbances. Through the theoretical analysis, all signals of the closed-loop control system are with the semi-globally uniform ultimate bounded (SGUUB) stability. The simulation experiments have been presented to verify the obstacle avoidance effectiveness and the burden-some superiority of the algorithm.

Robust Bearing-Based Formation Tracking Control of Underactuated Surface Vessels: An Output Regulation Approach

This article is concerned with the robust formation tracking control of a group of underactuated surface vessels whose formation is characterized by the relative bearings between the vessels. Control protocols are proposed to asymptotically steer certain points on the vessels, called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hand points</i> , which lie ahead of their centers of mass along the longitudinal axes, to track the desired moving formation; such a control method is called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">an output regulation approach</i> . The moving formation is guided by the motions of two or more agents, which are referred to as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">leaders</i> , and the other <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">follower</i> agents track the leaders by maintaining bearing constraints to neighbors. The proposed control schemes are designed based on a backstepping technique and sliding mode control. The latter is employed to attenuate known bounded disturbances present in the vessels' dynamics. When the bounds of the disturbances are unknown, an adaptive control protocol is subsequently investigated, under which the system is shown to converge to a small neighborhood of the target formation. Further, sufficient conditions on the upper bound of the hand points' desired velocities are provided for the uniform ultimate boundedness of the vessels' internal sway-yaw dynamics. Simulation results are provided to support the theoretical analysis.

Event-triggered path tracking control with obstacle avoidance for underactuated surface vessel compliant with COLREGs-constraints: Theory and experiments

Event-triggered path tracking control with obstacle avoidance for underactuated surface vessel compliant with COLREGs-constraints: Theory and experiments

Event-triggered trajectory tracking control of underactuated surface vessels with performance-improving mechanisms under input saturation and actuator faults

This paper deals with the improvement for the tracking performance of underactuated surface vessels (USVs) under input saturation and actuator faults. The neural networks (NNs) are used to reconstruct the dynamic uncertainty of the ship, and an adaptive law is designed to compensate the adverse effects of external unknown disturbances and bias faults on the system. To improve the tracking performance of the system, a nonlinear link is added in the design process of the control scheme to adjust the system error feedback, and the finite-time control (FTC) technology is used to further improve the steady-state performance and transient performance of the system. In addition, to solve the problem of communication resource limitation, an event-triggered mechanism for switching thresholds is introduced, which reduces the update frequency of controller signals. Based on the above techniques, a trajectory tracking control scheme with a performance improvement mechanism is designed. A rigorous stability analysis is provided for the control scheme using Lyapunov stability theory. Finally, the effectiveness of the control scheme is verified by two sets of simulations.

Adaptive Finite-Time Trajectory Tracking Event-Triggered Control Scheme for Underactuated Surface Vessels Subject to Input Saturation

In this paper, the trajectory tracking problem of underactuated surface vessels (USVs) that is subject to input saturation, unmodeled dynamics, and marine environmental disturbances is investigated. Firstly, USVs underactuation problem is handled by constructing a coordinate transformation. An auxiliary dynamic system is adopted to deal with input saturation. The adaptive law is presented to online update the upper bounds of the composite disturbances. The event-triggering condition is introduced to reduce drastically control execution frequency and the transmission load. By combining the auxiliary dynamic system, an adaptive technique, a first-order command filtered technique and an event-triggered condition, a novel adaptive finite time event-triggered control (AFETC) scheme is proposed, which has the following significant characteristics compared to most existing schemes: 1) the artfully constructed coordinate transformation not only avoids computational complexity but also simplifies the design; 2) the first-order command filtering vector-backstepping control method not only circumvents “explosion of complexity” in the traditional backstepping approach, but also ensures the finite-time settling of position tracking errors of USVs; 3) with the event triggered control, it reduces the control execution frequency, thereby decreasing the communication transmission load; and 4) it ensures stable tracking without requiring a priori information of the unmodelled dynamics of USVs or external disturbances. The designed robust adaptive control has proven to enable USVs to track the desired trajectory while guaranteeing the closed-loop stability in a finite time and avoiding Zeno behavior. Simulation and comparation results demonstrate the effectiveness and superiority of the proposed control strategy.

Distributed formation tracking control of underactuated surface vehicles based on event-trigged control

In this paper, a distributed formation tracking control problem is investigated for underactuated surface vessels (USVs). The uncertainties induced by model uncertainties and external disturbances are assumed to be unknown. An event-trigged disturbance observer (ETDO) is proposed to provide the estimations of the uncertainties, and an event-triggered mechanism is used to determine when measured velocity information must be sent to the observer. An event-trigged controller (ETC) is designed based on a backstepping technique, dynamic surface control, and the observer. Stability analysis of distributed formation control system is given to prove all signals are bounded. Simulations demonstrate the proposed control strategy.

Leader–Follower Formation Tracking Control of Underactuated Surface Vehicles Based on Event-Trigged Control

This paper investigates the leader–follower formation tracking control of underactuated surface vessels (USVs) with input saturation. Each vessel is subject to the uncertainties induced by model uncertainties and environmental disturbances. First, an event-triggered extended-state observer (ETESO) is used to recover the velocity, yaw rate and uncertainties. Then, an estimator is used to estimate the velocity of the leader. An event-triggered controller (ETC) is constructed based on the estimator, the observer and extra variables. Specifically, extra variables are used to solve the problems of underactuation and input saturation. Stability analysis of the control system is conducted to prove that all signals are bounded. Simulations demonstrate that the ETESO can accurately estimate the uncertainties, velocity and yaw rate, and the ETC can largely reduce the action times of actuator.

Prescribed performance control of underactuated surface vessels' trajectory using a neural network and integral time-delay sliding mode

Prescribed performance control of underactuated surface vessels' trajectory using a neural network and integral time-delay sliding mode

FXESO based FNMPC path following control for underactuated surface vessels with roll stabilisation

External ocean disturbances result in the roll motion of underactuated surface vessels (USVs), which probably have severe effects. To improve the USV capability of path following and speed maintenance in rudder roll stabilisation (RRS) control, a fixed-time extended state observer (FXESO) based fuzzy nonlinear model predictive control (FNMPC) scheme was proposed. A 4-degrees of freedom (DOF) nonlinear USV model is established for investigation. Subsequently, the FXESO is designed to estimate the velocity states and lumped disturbance terms of the USV model, which are used to simplify the predictive model. Subsequently, the disturbance compensation nonlinear model predictive control (NMPC) with fuzzy rules is designed to handle multi-objective cooperative control problems between path following and RRS. Fuzzy rules are designed to improve the performance of path following and speed maintenance by altering the objective function weights in MPC. The stability of proposed scheme was theoretically proven. The effectiveness of proposed algorithm was verified through simulations and comparisons.