Tracking Control Of Ships Research Articles

Safety-Critical Parallel Trajectory Tracking Control of Maritime Autonomous Surface Ships Based on Integral Control Barrier Functions

Safety-Critical Parallel Trajectory Tracking Control of Maritime Autonomous Surface Ships Based on Integral Control Barrier Functions

Event-Triggered Adaptive Neural Network Trajectory Tracking Control For Underactuated Ships Under Uncertain Disturbance

Abstract An adaptive neural network (NN) event-triggered trajectory tracking control scheme based on finite time convergence is proposed to address the problem of trajectory tracking control of underdriven surface ships. In this scheme, both NNs and minimum learning parameters (MLPS) are applied. The internal and external uncertainties are approximated by NNs. To reduce the computational complexity, MLPs are used in the proposed controller. An event-triggered technique is then incorporated into the control design to synthesise an adaptive NN-based event-triggered controller with finite-time convergence. Lyapunov theory is applied to prove that all signals are bounded in the tracking system of underactuated vessels, and to show that Zeno behavior can be avoided. The validity of this control scheme is determined based on simulation results, and comparisons with some alternative schemes are presented.

DDPG based LADRC trajectory tracking control for underactuated unmanned ship under environmental disturbances

Realizing trajectory tracking control of underactuated unmanned ships is critical for safe and stable navigation during offshore operations. The principal difficulties of this task lie in the coupling problem caused by the underactuated system and the uncertainty caused by the modeling error, internal parameter perturbations, and external environment. In this paper, a three-degree-of-freedom ship model is first built based on the manipulative modeling group equation. Then, a trajectory tracking line-of-sight guidance law is proposed to achieve the desired heading angle and forward speed during trajectory tracking, and the Lyapunov function is used to analyze its stability. Furthermore, the heading angle controller and forward speed controller are designed based on the linear active disturbance rejection control framework. In addition, to solve the challenging problem of controller parameter tuning and further improve the controller’s robustness, the Deep Deterministic Policy Gradient algorithm is applied to adjust the controller parameters. Finally, the effectiveness of the proposed method is verified by the simulation results of sinusoidal, circular, and square trajectories with wind and current disturbances.

Event-Triggered Asymptotic Tracking Control of Underactuated Ships With Prescribed Performance

Adapting to the navigational high-precision tracking tasks, this paper develops an event-triggered adaptive neural asymptotic tracking control framework for underactuated ships. The prescribed performance control (PPC) technique is employed to address spatial constraints in navigation, where the positional tracking errors are transformed via the transformation functions. By using the approximation of radial basis function neural networks (RBF NNs) in the form of minimum learning parameters (MLPs), the uncertainties coming from the unknown model dynamics, the environmental disturbances and the derivation of virtual control laws are offset all together, and a succinct computation is guaranteed. Assisted by the property of neural basis function, the “algebraic loop” problem in the backstepping design is released. To achieve the asymptotic tracking performance, the hyperbolic tangent functions are incorporated into the control laws, which are characterized by the integral-bounded terms. The event-triggered control (ETC) is designed in the controller-to-actuator (CA) channel. Two separate triggering conditions are constructed for the surge and the yaw motions respectively, which are characterized by the compound thresholds composed of a variable and a constant. The “Zeno” behaviors can thereby be avoided. The proposed scheme has three notable characteristics: 1) the computational complexity is reduced by using the MLP technique with lumped uncertainties; 2) the high-precision tracking performance can be achieved through the asymptotic tracking control; 3) the practical problems of spatial constraints and communication burdens can be solved by fabricating a uniform control framework including PPC and ETC. With the aid of direct Lyapunov candidates and the Barbalat’s lemma, the asymptotic convergence of all the tracking errors is proved. Finally, a numerical experiment corroborates the feasibility of the proposed scheme.

Nonlinear observer-based adaptive output feedback tracking control of underactuated ships with input saturation

Nonlinear observer-based adaptive output feedback tracking control of underactuated ships with input saturation

Data-Driven Adaptive Disturbance Observers for Model-Free Trajectory Tracking Control of Maritime Autonomous Surface Ships.

In this article, we address the disturbance/ uncertainty estimation of maritime autonomous surface ships (MASSs) with unknown internal dynamics, unknown external disturbances, and unknown input gains. In contrast to existing disturbance observers where some prior knowledge on kinetic model parameters such as the control input gains is available in advance, reduced- and full-order data-driven adaptive disturbance observers (DADOs) are proposed for estimating unknown input gains, as well as total disturbance composed of unknown internal dynamics and external disturbances. An advantage of the proposed DADOs is that the total disturbance and input gains can be simultaneously estimated with guaranteed convergence via data-driven adaption. We apply the proposed full-order DADO for the trajectory tracking control of an MASS without kinetic modeling and present a model-free trajectory tracking control law for the ship based on the DADO and a backstepping technique. We report the simulation results to substantiate the efficacy of the proposed DADO approach to model-free trajectory tracking control of an autonomous surface ship without knowing its dynamics.

Adaptive Neural Output Feedback Tracking Control of Underactuated Ships Against Uncertainties in Kinematics and System Matrices

Adaptive neural output feedback tracking control is developed for underactuated ships with uncertainties in kinematics (i.e., kinematic uncertainties) and uncertain off-diagonal terms in the matrices of their system dynamics (i.e., dynamic uncertainties), where radial basis function networks are incorporated. As the kinematic uncertainties unavoidably exist in the off-diagonal terms of system matrices and only the posture information (position variables and yaw angle) of the ship is available, the velocities should be observed and the kinematic and dynamic uncertainties should be simultaneously compensated to achieve the satisfactory ship tracking control performance. Therefore, the kinematic and dynamic uncertainties of the underactuated ship are rigorously derived. The kinematic equations with uncertainties are then derived such that the proposed nonlinear velocity observer can be used to estimate the combined velocities and kinematic uncertainties using the posture information irrespective of the ship dynamics. The dynamic uncertainties are also derived while taking into consideration the uncertainties in the system matrices. An adaptive neural uncertainty observer is then proposed to estimate the dynamic uncertainties. In this way, the proposed adaptive neural output feedback control law can compensate for the uncertainties in both the kinematics and dynamics. The estimation errors in the combined velocities and kinematic uncertainties and the dynamic uncertainties are rigorously considered in the proposed controller design. A stability analysis and the simulation results of the ship tracking control system are provided to demonstrate the validity of the proposed method.

Design of Cooperative Output Regulators for Heterogeneous Uncertain Nonlinear Multiagent Systems.

Cooperative output regulation (COR) of multiagent systems having heterogeneous uncertain nonlinear dynamics is often challenging because of the complex system dynamics and the coupling among agents. This article develops an adaptive internal model-based distributed regulator such that the outputs of a network of nonlinear agents are all regulated to a reference despite external disturbances. Specifically, we consider heterogeneous agents having nonlinear strict-feedback forms, with nonidentical unknown control directions, and subject to an unknown linear exosystem. Addressing the nonlinear COR problem shows the capability and flexibility of the proposed output regulator. The simulation results of output synchronization of Lorenz systems and cooperative tracking control of multiple ships are presented to show the capability of the proposed regulator.

Extrapolation Algorithm of Ship Track Smoothing Based on Spline Theory

Zhao, X. and Song, X., 2020. Extrapolation algorithm of ship track smoothing based on spline theory. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 909–912. Coconut Creek (Florida), ISSN 0749-0208.Due to the poor transition effect of traditional ship track control, the shipping pressure is too large. The research on extrapolation algorithm of ship track smoothing based on spline theory is proposed. Based on the principle of spline fitting, a three degree of freedom motion model of ship's horizontal plane is established to analyze the force on the ship in the process of motion, so the motion equation is obtained. The extrapolation algorithm is used to analyze the intersection of wave gates. Considering the actual situation and the influence parameters, the research on extrapolation algorithm of ship track smoothing based on spline theory is completed. The control experiment is designed to compare the track control effect of the proposed algorithm with that of the traditional algorithm. The results show that the combination of the spline theory and the extrapolation method results in a higher fit between the control curve and the actual route, which is obviously superior to the traditional results, and the control effect of the ship track is optimized.

Design of Autonomous Obstacle Avoidance Unmanned Boat System for Wetland Monitoring

In view of the drastic reduction of wetland area, serious pollution, low efficiency of prior art and many factors, this paper proposes an autonomous obstacle avoidance unmanned boat system design for wetland monitoring. The system adopts D* algorithm and improved LOS guidance law to realize unmanned ship track control and global path planning, and combines Yolov3 algorithm for target recognition and partial data acquisition during navigation to achieve autonomous obstacle avoidance navigation. The sensor is used to collect the wetland environment information and upload it to the shore monitoring centre to complete the automatic data collection and monitoring of the wetland. The system can improve the efficiency and quality of wetland monitoring, reduce labor costs, and can be widely used in wetland monitoring automation, marine environment monitoring, and cloud service platforms.

Adaptive nonlinear ship tracking control with unknown control direction

SummaryThis paper is to suggest a novel design for ship tracking control of the benchmark Norrbin nonlinear ship model under relaxed conditions. The challenges of the problem under investigation include the uncertain or absent information of the model time constant, the uncertain reference course, and the intrinsic environmental disturbances. We formulate the ship tracking control problem in terms of a nonlinear output regulation problem with unknown control direction and uncertain exosystems. To solve the problem, we first adopt a novel internal model candidate to convert the output regulation problem into a stabilization problem for an augmented system. Then, a Nussbaum‐gain‐based stabilizer is developed for the augmented system to complete the design. Simulation results are presented to show the effectiveness of the proposed controller.

Trajectory exponential tracking control of unmanned surface ships with external disturbance and system uncertainties

Any unmanned surface ship is subject to system uncertainty, unknown parameters, and external disturbance induced by the wind, the wave loads, and the ocean currents. They may deteriorate ship's control accuracy. This paper aims to solve the trajectory tracking control problem of unmanned surface ships with disturbance and system uncertainty accommodated simultaneously. An estimator-based backstepping controller is presented with an estimator designed to provide a precise estimation of the disturbance and uncertainties. The proposed controller ensures the closed-loop tracking system to be globally exponentially stable. The trajectory tracking error and the estimation error of disturbance and uncertainties are globally exponentially stable. The key feature of the developed control scheme is that it is more robust to disturbances and system uncertainties. Simulation results are further presented to validate the effectiveness of the approach.

Robust Tracking Control and Stabilization of Underactuated Ships

AbstractThis paper addresses the problem of tracking control and stabilization for underactuated ships subjected to parametric modeling uncertainties. By designing a novel error state transformation scheme, some auxiliary variables are provided to be regarded as additional virtual control signals, while these variables can change their structures for different reference trajectories. Then, a robust control scheme is presented to achieve practical convergence of tracking errors and the ship's velocities to bounded neighborhoods of the origin. Simulation results are performed to illustrate the effectiveness of the proposed control scheme.

Tracking Control of Surface Ships With Disturbance and Uncertainties Rejection Capability

This paper investigates a difficult problem of tracking control manipulation for surface ships. External disturbances and system uncertainties are simultaneously addressed. The tracking law design is accomplished in a framework of backstepping control. First, a backstepping-based controller is presented to achieve trajectory tracking with desired tracking performance guaranteed. On the basis of this baseline feedback control law, an adaptive version of this controller is further synthesized to handle the uncertainties and disturbances. It is shown by the Lyapunov stability analysis that the closed-loop tracking system is guaranteed to be asymptotically stable. The desired trajectory is successfully followed with the tracking error asymptotically converging to zero. The effectiveness of the controller is validated through a numerical example.

Global stable tracking control of underactuated ships with input saturation

In this paper, tracking control of underactuated ship in the presence of input saturation is addressed. By dividing the tracking error dynamic system into a cascade of two subsystems, the torques in surge and yaw axes are designed separately using the backstepping technique. More specifically, we design the yaw axis torque in such a way that its corresponding subsystem is finite time stable, which makes it to be de-coupled from the second subsystem after a finite time. This enables us to design the torque in the surge axis independently. It is shown that the closed-loop system is stable and the mean-square tracking errors can be made arbitrarily small by choosing design parameters. Simulation results also verify the effectiveness of the proposed scheme.

Formation tracking and attitude synchronization control of underactuated ships along closed orbits

SummaryThis article considers the problem of directing a family of underactuated ships to formation tracking a set of closed orbits and achieve attitude synchronization. It shows that our previous concentric compression design can be extended to deal with a general kind of non‐convex, closed curves and the coordinated motion of underactuated ships. The condition of nonzero total linear speed of each ship is ensured by a potential function. Under the bidirectional communication topology, asymptotical stabilization is proved with the help of the invariance‐like theorem and the extension of Barbalat's lemma. Theoretical results are proved by the numerical examples. Copyright © 2014 John Wiley & Sons, Ltd.

The Development of Marine Autopilot Simulator

The mathematical model of the ship autopilot system is established which centering on marine hydraulic steering gear, based on the Nomoto ship motion model, and considered the influence of wind, wave, flow and other environmental factors on ship course angle. Depend on this model, the physical-digital hybrid simulation autopilot simulator is developed. This simulator has all of the operating functions of the ship steering system, it can not only simulate the turbine engine working scenarios, but also dynamically display the operation process, and the simulator is applicable to the ship track control research and crew training work.

Straight-Line Trajectory Tracking Control for Sampled-Data Underactuated Ships

Straight-line trajectory tracking control of sampled-data underactuated ships with both state and output feedback controllers is considered and analyzed by resorting to a nonlinear sampled-data control theory. State feedback controllers and reduced-order observers are designed on the basis of the Euler approximate models. Then they are combined to obtain output feedback controllers that semiglobally practically uniformly asymptotically stabilize the tracking error dynamics. Both simulation and experimental results are given to show the efficiency of the designed controllers.

Nonlinear Time Series Model for Ship Tracking Control

This paper presents two models for representing the ship's tracking dynamic behavior. The first model is a hybrid model combined by a state-dependent nonlinear time series model and a ship moving equation model, which has the advantage in long-term prediction. The second model is a pure state-dependent time series model, which has the advantage in short-term prediction. Both of them showed better simulation results than the model presented in Peng et al. [2010] did.

Ship's tracking control based on nonlinear time series model

For actualization of ship tracking control along a desired path with a constant velocity, a hybrid model is proposed to represent the ship's tracking dynamic behavior. Firstly, a single-input single-output nonlinear time series model is built for characterizing the responses between the ship's heading angle deviation and its rudder angle. To represent nonlinearity of the ship motion, the rolling angle is used as the model index to make the model parameters vary with the ship sailing states considering the yaw-heel-effect. The nonlinear time series model is identified offline by using previously observed real data. Then, a state-space model combined with the relationship between the heading angle deviations and the cross track errors is proposed to represent the tracking dynamic behavior. On the basis of the identified state-space type tracking motion model, a predictive controller is designed to steer the ship sailing forward with the constant velocity along the predefined reference path. The effectiveness of the nonlinear time series model-based method for the tracking control proposed in this paper is demonstrated by simulation studies and actual experiments.