Ship Model Parameters Research Articles

Automatic berthing of unmanned surface vessels with predetermined performance

To solve the problem of ship automatic berthing control due to unknown time-varying disturbance and dynamic uncertainty of model parameters, an automatic berthing control law based on predefined performance time function is proposed. First, a predefined performance time function is designed and coupled with tracking error to achieve the predetermined performance of tracking error. Secondly, radial basis function neural network is used to approach the dynamic uncertainty of ship model parameters, and the complex uncertainty of model parameters and unknown time-varying disturbance is represented by linearized parameter form with single virtual parameter, which makes the calculation simple and easy to implement in engineering. On this basis, the reverse step control law is designed. Thirdly, the stability of the system is proved based on Lyapunov stability theory. Finally, the simulation results show that the control law can make the ship reach the desired position and heading angle, and realize the automatic berthing of the ship. The control law and berthing controller designed in this paper have good applicability and robustness, which provides a theoretical basis for the subsequent control research of surface intelligent ships.

A new identification algorithm for ship model parameters based on sinusoidal function processing innovation

Objectives Due to the few data samples of ship test a, it is difficult to identify ship model parameters quickly and accurately. Methods On the basis of the original least-squaresystem identification algorithm, the innovation is processed by sinusoidal function, and a new method of parameter identification for ship model based on nonlinear sinusoidal function is proposed. Results The Yukun ship, a teaching and training ship of Dalian Maritime University, is taken as an example to carry out the identification experiment, In the case of only 26 sets of test data, the identification effect of the original least square method and improved least square algorithm is compared. The simulation results show that the parameter identification accuracy of the improved algorithm is improved by about 15%, and the effectiveness of the algorithm is verified by using the Yupeng ship. Conclusions This algorithm provides reference of parameter identification of ship model with few data samples.

Simulation of a Ship’s Deperming Process Using the Jiles–Atherton Model

Demagnetization of ferromagnetic vessels, or deperming, is a common practice used to reduce the magnetic signature. The general approach for ship deperming presented in the literature is the anhysteretic protocol, where the applied field is reduced at equidistant intervals. In reality, the method involves the complications of having a bias (Earth's magnetic) field present and the practical impossibility of magnetizing the ship to saturation. When anhysteretic demagnetization cannot be applied, past experience is used to empirically estimate the necessary magnetic treatment for each vessel. In this article, we examine the ship deperming on a fundamental basis by describing it using the Jiles-Atherton (J-A) model. The ship model parameters were estimated by inversion from measurements taken at certain points of the demagnetization cycle. The model is useful for testing different protocols of, in general, not-unique deperming operation. The proposed J-A analysis of hysteresis offers a theoretical basis to predict the demagnetization results a priori. The model simulation study of the demagnetization process is demonstrated with the measurements from HMCS Toronto.

An improved nonlinear innovation-based parameter identification algorithm for ship models

AbstractTo solve the problem of identifying ship model parameters quickly and accurately with the least test data, this paper proposes a nonlinear innovation parameter identification algorithm for ship models. This is based on a nonlinear arc tangent function that can process innovations on the basis of an original stochastic gradient algorithm. A simulation was carried out on the ship Yu Peng using 26 sets of test data to compare the parameter identification capability of a least square algorithm, the original stochastic gradient algorithm and the improved stochastic gradient algorithm. The results indicate that the improved algorithm enhances the accuracy of the parameter identification by about 12% when compared with the least squares algorithm. The effectiveness of the algorithm was further verified by a simulation of the ship Yu Kun. The results confirm the algorithm's capacity to rapidly produce highly accurate parameter identification on the basis of relatively small datasets. The approach can be extended to other parameter identification systems where only a small amount of test data is available.

Error-driven-based adaptive nonlinear feedback control of course-keeping for ships

This paper presents a robust adaptive nonlinear feedback algorithm based on error-driven function for ships course-keeping which are subjected to the unknown time-varying disturbances, uncertain ship model parameters and control saturation. Nonlinear feedback and adaptive techniques are used to design the control law. The error-driven function is designed to avoid the input saturation and adjust the control gain. The designed adaptive law not only achieves the self-regulation of course-keeping control system but also adjusts parameters adaptively. In addition, the Lyapunov direct method is utilized to analyze the stability of course-keeping system. Theoretical analysis indicates that the designed control law can achieve the ship course-keeping while ensuring that all signals are bound. Finally, the effectiveness of the developed control strategy is demonstrated by simulations and comparative results.

Analysis of Impact of Ship Model Parameters on Changes of Control Quality Index in Ship Dynamic Positioning System

Abstract In this work there is presented an analysis of impact of ship model parameters on changes of control quality index in a ship dynamic positioning system designed with the use of a backstepping adaptive controller. Assessment of the impact of ship model parameters was performed on the basis of Pareto-Lorentz curves and ABC method in order to determine sets of the parameters which have either crucial, moderate or low impact on objective function. Simulation investigations were carried out with taking into account integral control quality indices.

Identification of ship mathematical model parameters for support of automatic control in voyage conditions

An approach to identifying the ship motion mathematical model and disturbance parameters in voyage conditions is presented in the paper. The approach is intended for use under constraints during the voyage, i.e., under off-course restrictions and during the voyage in the appointed limited-width corridor. To determine the ship model parameters and static disturbance moment value, it was proposed to use spectral analysis of the angular velocity signal. The formulas and test procedure for identifying the model parameters, along with practical recommendations on the approach implementation were given in the paper. The simulation results show that the accuracy of parameters allows to use these data for the autopilot controller synthesis and adjustment. Thus, the rudder deviation angle may be of about one degree, so the ship deviates from the course only by a small angle during the identification process. Tests on the high seas have proved that the proposed approach can be practiced.

A nonlilear controller for ship autopilots

Conventional ship autopilots are designed based on a linear ship model using pole - placement technique or linear optimal theory. However, in operation, the ship kinematical parameters can go out the linear limits. In this paper, a nonlinear optimal control law based on aggregated variables is presented. The criterion is chosen so that the dynamic characteristics of object are included. The stability of the closed-loop system is global according to the Lyapunov stability theory. The control law depends explicitly on ship model parameters, so that it is can be easily to tune when the parameters change.

Roll Damping and Anti-Capsizing System for Ships Using Fuzzy-Extension Control Strategy

Rolling is an undesirable motion for ships. Large amplitude rolling can easily lead to capsize which will cause the loss of life and property. This paper proposes a fuzzy-extension control strategy for ship roll damping and anti-capsizing system. Fuzzy control strategy is studied in the classical domain for rudder roll stabilization to solve uncertainties in quantitative change and gradual change resulting from the change of ship model parameters so as to improve control performance. Moreover, the real-time tuning algorithm is presented to tune the fuzzy rules. Extension control strategy is studied in extension domain to solve the uncertainties in non-gradual change arising from the wave so as to extend anti-capsizing control sphere. Every control strategy can realize effective control within the scope of control.The two intelligence control methods are combined to increase the level of intelligence of system. This paper carries out the simulation under various situations such as different navigation speed, sea conditions, encounter angle and ship parameter perturbation, to test the roll reduction and robustness of the roll controller designed.

Parameters identification for ship motion model based on particle swarm optimization

PurposeThe purpose of this paper is to identify the Nomoto ship model parameters accurately, in order to produce a very close match between the predictions based on the model and the full‐scale trials.Design/methodology/approachVarious ship maneuvering mathematical models have been used when describing the ship dynamics behavior. The Nomoto ship model is a class of simplified hydrodynamic derivative type models which are the most widely used, accepted and perhaps well developed. To determine the model parameters accurately, particle swarm optimization (PSO) is chosen as an evolution algorithm in this paper. This arithmetic can guarantee the convergence and global optimization ability, and avoid sinking into a local optimal solution.FindingsThe process of PSO for identifying the Nomoto ship model parameters is given.Research limitations/implicationsAvailability of the full‐scale trial data are the main limitations.Practical implicationsThe ship model parameters provide very useful advice in ship's autopilot process.Originality/valueThe paper presents a new parameter identification method for the second‐order Nomoto ship model based on PSO.

Identification of Nonlinear Ship Model Parameters Based on the Turning Circle Test

This work presents a contribution to solving the problem of identification of ship model parameters using the experimental results from a particular trial test. The innovation of this paper lies in the fact that for this identification purpose it is necessary to know only the turning radius that describes the ship during the performance of the turning test trial. A relatively complex nonlinear model of Norrbin has been chosen as a basis because it represents the ship's dynamics appropriately, as proven through experimental measurements obtained during the course change test. The proposed algorithm of identification of the four ship model parameters is based on an adaptive procedure and the backstepping theory. Another additional coefficient can be determined by an alternative procedure. The knowledge of the true values that characterize the dynamic of a ship is fundamental in the ship steering control that is carried out by autopilots. The simulation results show the suitability of the proposed procedure.

Identification of the nonlinear ship model parameters based on the turning test trial and the backstepping procedure

This work presents a novel contribution to solve the problem of identification of ship models parameters using the temporal variation data of the yaw angle achieved from a particular trial test as the turning circle. A relatively complex nonlinear model of Wagner-Smith has been chosen as basis because it represents the ship's dynamics appropriately as proved through the experimental measures obtained in a particular ship. The proposed algorithm of identification of the six ship model parameters is based on the combination of two sub-algorithms: the backstepping procedure and the tuning design method. The simulation results show the suitability of the proposed procedure.

Adaptive ship steering autopilot design with saturating and slew rate limiting actuator

The proposed adaptive ship steering autopilot is based on the internal model control method, which is characterized by a model-based design approach that provides clear connections between the structure of the controller and that of the ship model. Specifically, the controller parameters depends explicitly on the ship model parameters and on a design parameter that specifies the closed-loop system response speed. Once the ship model parameters are estimated on-line, the controller parameters are adjusted accordingly to adapt to different operating conditions. A key feature of the proposed approach being that the rudder limit and rudder rate limit are directly taken into the adaptation design consideration. Specifically, a reference conditioning technique that modifies the reference input in such a way that the rudder command is always equal to the actual rudder input into the plant. This allows the controller to exert its full power without attempting to take on values beyond the bounds imposed by the rudder limit and rudder rate limit. Consequently, under different operating conditions, rapid course-changing manoeuvres are achievable without introducing possible instability problem caused by the controller integrator wind-up. Copyright © 2000 John Wiley & Sons, Ltd.

Adaptive Ship Steering Autopilot Design with Saturating and Slew Rate Limiting Actuator

The proposed adaptive ship steering autopilot is based on the internal model control method, which is characterized by a model-based design approach that provides clear connections between the structure of the controller and that of the ship model. Specifically, the controller parameters depends explicitly on the ship model parameters and on a design parameter that specifies the closed-loop system response speed. Once the ship model parameters are estimated on-line, the controller parameters are adjusted accordingly to adapt to different operating conditions. A key feature of the proposed approach being that the rudder limit and rudder rate limit are directly taken into the adaptation design consideration. Specifically, a reference conditioning technique that modifies the reference input in such a way that the rudder command is always equal to the actual rudder input into the plant. This allows the controller to exert its full power without attempting to take on values beyond the bounds imposed by the rudder limit and rudder rate limit. Consequently, under different operating conditions, rapid course-changing maneuvers are achievable without introducing possible instability problem caused by the controller integrator wind-up.

A New Nonlinear Adaptive Autopilot for Ships

Abstract An autopilot design project is presented. The design is based on a nonlinear ship model. This nonlinear ship model explains the results obtained from the standard ship manoeuvering tests. Controller parameters are computed as a function of the linearized ship model parameters. The autopilot adapts to changing dynamics by using gain scheduling. A nonlinear modified second order filter is used to filter the wave induced movements from the measurements. The autopilot is tested in a realistic simulation environment.