Control Of Underactuated Surface Vessels Research Articles

Guiding vector field and self-structuring learning network-based formation control of underactuated surface vessels in static obstacle environments with flexible performances

To address the problem of underactuated surface vessel (USV) formation control in static obstacle environments with model uncertainties and time-varying external disturbances, a model-free formation control strategy is proposed in this paper. First, based on the guiding vector field (GVF), a composite GVF is developed to guide USV formation to the desired position and to avoid multiple static obstacles. Second, a flexible constraint strategy is introduced, and the constraint boundary conditions are appropriately relaxed to avoid singularities in the obstacle environment. Then, based on the Mexican hat wavelet function, the self-structuring fuzzy Mexican hat wavelet cerebellar model articulation controller (SCMAC), and a self-structuring fuzzy Mexican hat wavelet brain emotional learning controller (SBELC), are proposed to achieve model-free control. In addition, the self-structuring algorithm is embedded into SCMAC and SBELC to achieve autonomous optimization of the controller structure and to reduce the computational effort of the control system. The salient features in the proposed control strategy are as follows. First, the proposed model-free formation control strategy does not have to rely on accurate model information. Second, collisions are effectively avoided, and good control performance is guaranteed even under the influence of disturbances and static obstacles. Third, the proposed self-structuring algorithm achieves automatic construction of the controller structure. Finally, the signals in the control system are proven to be bounded, and the simulation results verify the feasibility and superiority of the proposed model-free control strategy.

Quasi-Infinite Horizon Model Predictive Control with Fixed-Time Disturbance Observer for Underactuated Surface Vessel Path Following

As a flexible, autonomous and intelligent motion platform, underactuated surface vessels (USVs) are expected to be an ideal means of transport in dangerous and complex marine environments. The success and efficiency of maritime missions performed by USVs depend on their ability to accurately follow paths and remain robust against wind and wave disturbances. To this end, this paper focuses on accurate and robust path following control for USVs under wave disturbances. Model predictive control with a quasi-infinite horizon is proposed which converts the objective function from an infinite horizon to an approximate finite horizon, providing the convergence performance in long prediction horizons and reducing the computation load explicitly. To enhance robustness against disturbances, a fixed-time disturbance observer is applied to estimate the time-varying and bounded disturbances. The estimated value is provided to the controller input to form a robust control framework with disturbance feedforward compensation and predictive control feedback correction, which is substantially different from existing works. The convergence and optimality of the proposed algorithm are presented mathematically. Finally, we demonstrate the advantages of the algorithm in both theory and simulation.

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.

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.

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.

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

Event-Triggered Optimal Tracking Control for Underactuated Surface Vessels via Neural Reinforcement Learning

Event-Triggered Optimal Tracking Control for Underactuated Surface Vessels via Neural Reinforcement Learning

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 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.

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.

Fixed-time self-structuring neural network fault-tolerant tracking control of underactuated surface vessels with state constraints

In this paper, a fixed-time fault-tolerant control strategy is proposed for trajectory tracking of underactuated surface vessels (USVs) with input saturation. A predefined region boundary function is proposed, which has all predefined fixed-time convergence properties and provides predefined specifications for tracking errors. To achieve the predetermined tracking performance, a fixed-time adaptive neural network state constrained fault-tolerant controller is proposed based on dynamic surface control technology, a back-stepping program, and an asymmetric time-varying tangent barrier Lyapunov function (ATVTBLF). The unknown external environment disturbances and complex continuous unknown nonlinear terms are approximated by a self-structuring neural network (SSNN), which can improve the robustness of the control system to unknown parameters and guarantee the tracking performance of the control system. The number of neurons of the SSNN can be adjusted online according to the approximation efficiency, which can reduce the amount of calculation of the control system. Based on Lyapunov stability theory, it is proven that the closed-loop system is bounded and stable in a fixed time, and the tracking error is always kept within the constraint range. The simulation results show that the underactuated surface vessel control system has good tracking performance.

Minimum-learning-parameter-based adaptive finite-time trajectory tracking event-triggered control for underactuated surface vessels with parametric uncertainties

For the problem of trajectory tracking control of underactuated surface vessels (USVs) affected by input saturation, parametric uncertainties, time-varying marine environmental disturbances, and limited transmission resources, a robust adaptive finite-time event-triggered control scheme is presented in this paper. First, a coordinate transformation is constructed to tackle the underactuation problem of the USV and enables the USV control law to be devised in vector form, which simplifies the design and makes it more suitable for computer processing. A continuous auxiliary dynamic system is constructed to handle the input saturation problem. The minimum learning parameter (MLP) technique is used to approximate the parametric uncertainties of the model. An adaptive law is devised to update online the upper bound of the combination of external disturbances and the approximation error generated by the MLP. Additionally, a finite-time control scheme is presented by introducing a robustifying term in the virtual control law, which improves the control performance; an introduced event triggering mechanism in the channel from the controller to the actuator decreases both the transmission burden and the control execution frequency without affecting the control performance. The theoretical analysis reveals that the devised robust adaptive finite-time event-triggered control scheme enables the USVs to track the desired trajectory in a finite time with a small number of control executions, while ensuring the closed-loop stability of the system and avoiding Zeno behavior. The simulations verify the effectiveness and the superiority of the presented control scheme.

ESHLOS guidance for neuro-adaptive path following control of underactuated surface vessels

This paper proposes a neuro-adaptive path following control scheme based on ESHLOS guidance law for underactuated surface vessels with unmeasured linear velocities. Based on two extended state observers, an ESHLOS guidance law is designed, where the guidance law not only calculates the desired heading angle and surge velocity signals, but also compensates the unknown sideslip angle. Then, neuro-adaptive path following controllers are proposed to track the desired signals via backstepping technique. The hyperbolic tangent function is applied to model input saturation nonlinearity, and adaptive radial basis function neural networks are used to offset the lumped disturbances including external environmental disturbances, model uncertainties. Besides, a high-order tracking differentiator is introduced to generate derivatives of desired heading angle, so that the computational burden inherent in backstepping technique is reduced. Based on the Lyapunov functions, it is proven that all error signals of the closed-loop system are bounded. Finally, simulation results are utilized to reveal the efficacy of the presented approach.

Distributed observer based event‐triggered affine formation maneuver control for underactuated surface vessels with positive minimum inter‐event times

AbstractThis article investigates the distributed event‐triggered affine formation maneuver control problem for multiple underactuated surface vessel (USV) systems with positive minimum inter‐event times (MIET). Unlike common formation control methods that only ensure the formation system to keep a fixed geometric shape, the proposed scheme enables multiple USVs maneuver as a group in translation, shearing, rotation, or combinations of them. The proposed control strategy is composed of two parts. First, a distributed event‐triggered observer (DETO) is proposed to observe the time‐varying target formation under the lack of global leaders' information and govern the inter‐vessel communications among the formation group. Besides, the MIET of the designed communication strategy is proved to be strictly positive and computable from formation configurations and control parameters. With these guarantees, the maximum communication frequency can be known in advance. Then, upon the DETO signals, the adaptive local tracking controller is subsequently synthesized for each vessel to realize the target formation track. Rigorous theoretical analysis and simulation results are finally conducted to verify the validness and effectiveness of the proposed algorithm.

Trajectory tracking for underactuated surface vessels with time delays and unknown control directions

The problem of trajectory tracking control for underactuated surface vessels with time-delays, model uncertainty and unknown control directions has been considered in this paper. Firstly, an integration time delayed sliding mode controller is proposed, which decomposes the underactuated non-linear system into a cascading system consisting of a kinematics subsystem and a dynamics subsystem. Secondly, an adaptive backstepping control method for the heading angle system is proposed, which can drive the heading angle error into a preset interval. Then the Bouc-wen model is used to describe the hysteresis of the system, Nussbaum gain function is adopted to deal with unknown control directions, and the adaptive controller is designed by combining error transformation with Lyapunov function. Furthermore, a suitable Lyapunov-Krasovsky function is selected to analyse and prove the global stability of the closed-loop system. Finally, some numerical simulations show the effectiveness of the presented control methods.

Improved ELOS based path following control for underactuated surface vessels with roll constraint

This study aims to the path following control of underactuated surface vessels with an improved extended state observer based line-of-sight (ELOS). The large roll motion and nonzero drift angle can affect the guidance law and the course tracking accuracy in rough waves, the two factors should be considered when the path following control system is designed. The robustness of the tracking control system is enhanced by handling the system dynamic uncertainty and external random disturbances. First, the roll motion based track error dynamics are established, then a reduced order extended state observer is applied to estimate the time varying drift angle, and the adaptive heading guidance law is proposed. Finally, a robust adaptive heading control law is developed by combining dynamic surface control, sliding mode control and backstepping techniques. The ELOS based path following control methodology can ensure that all estimation and track errors are uniformly ultimately bounded. Simulations were used to illustrate the effectiveness of the proposed controller by comparing it with sliding mode control.