• Journal of Hydrospace Technology
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• v.1 no.1
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• pp.66-74
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• 1995

Unknown parameters can be determined by system identification techniques. Extended Kalman filter method was introduced as a real time estimator of hydrodynamic derivatives but it has the problem named the coefficient drift. In this study, 2nd order filter estimates hydrodynamic derivatives in Abkowitz model In order to reduce the coefficient drift, parallel processing is used. The measured state and ship trajectory are compared with the estimated values. Parallel processing of 2nd order filter gives very similar results to parallel processing of extended Kalman filter. Parallel processing cannot not remove the coefficient drift perfectly, but it reduces the estimation error.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.772-775
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• 1992

It is necessary to estimate hydrodynamic coefficients to design the auto-pilot system and motion simulator of submersible vehicle. In this paper, an algorithm was designed to estimate hydrodynamic coefficients of submersible vehicle. Using this algorithm, the hydrodynamic coefficients were estimated from measurements of full scale trial. The estimated hydrodynamic coefficients were used for the design of an auto-depth controller(ADC) of submersible vehicle, and the resulting ADC are proved to have a better performance than the previous one.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.2
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• pp.121-126
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• 1996

The hydrodynamic coefficients estimation (HCE) is important to design the autopilot and to predict the maneuverability of an underwater vehicle. In this paper, a system identification is proposed for an HCE of an underwater vehicle. First, we attempt to design the HCE algorithm which is insensitive to initial conditions and has good convergence, and which enables the estimation of the coefficents by using measured displacements only. Second, the sensor and measurement system which gauges the data from the full scale trials is constructed and the data smoothing algorithm is also designed to filter the noise due to irregular fluid flow without changing the data characteristics itself. Lastly the hydrodynamic coefficients are estimated by applying the measured data of full scale trials to the developed algorithm, and the estimated coefficients are verified by full scale trials.

• Journal of computational fluids engineering
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• v.20 no.2
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• pp.81-87
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• 2015

For Underwater vehicles, Unwanted roll excursions are inevitable as they are caused by induced propeller torque, disturbances, and banking motion during turns. To estimate the manoeuvring performance of underwater vehicle, it is necessary to obtain the roll coefficient of body. This paper was covered estimation of roll coefficient of underwater vehicle using STAR-CCM+, commercial CFD(Computational Fluid Dynamics) code. The RANS equations for incompressible fluid flows was solved numerically by using a finite volume method. An MRF(Moving Reference Frame) Method was Also adopted for rotations of body. For the validation, the flow around a DARPA SUBOFF bare hull model was simulated and good agreement with experiments was obtained. And Pure roll coefficients were calculated and campared with the experimental data which were presented by Seoul National University. Finally, an underwater vehicle model with propeller was simulated and analyzed for estimation of roll coefficient variation caused by induced propeller torque.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.10
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• pp.935-941
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• 2016

Predicting and evaluating ship manoeuvring characteristics are very important not only for the design stage, but also for the existing vessels. There are several ways to predict ship's manoeuvrability and most of them are highly connected with the estimation of hydrodynamic coefficients. This paper presents a new estimation method using the system identification with mathematical algorithms for estimating hydrodynamic coefficient in the ship's mathematical model. Specifically a double ended ferry which equips four azimuth propulsion systems were chosen as benchmark ship and a set of benchmark data which is generated in the fast time simulation software was provided to conduct mathematical optimization process. Also the initial values for the optimization were borrowed from the empirical regression formulas of the simulation software of Rheinmetall Defence ship simulator. Therefore the newly suggested mathematical optimization algorithm gave a successful result for estimation hydrodynamic coefficients. Proper optimization conditions of the objective function and constraints were also verified during the study.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.3
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• pp.258-265
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• 2017

This paper validates a system identification method using mathematical optimization using sea trial measurement data as a benchmark. A fast time simulation tool, SIMOPT, and a Rheinmetall Defence mathematical model have been adopted to conduct initial hydrodynamic coefficient estimation and simulate ship modelling. Calibration for the environmental effect of sea trial measurement and sensitivity analysis have been carried out to enable a simple and efficient optimization process. The optimization process consists of three steps, and each step controls different coefficients according to the corresponding manoeuvre. Optimization result of Step 1, an optimization for coefficient on x-axis, was similar compared to values applying an empirical regression formulae by Clarke and Norrbin, which is used for SIMOPT. Results of Steps 2 and 3, which are for linear coefficients and nonlinear coefficients, respectively, was differ from the calculation results of the method by Clarke and Norrbin. A comparison for ship trajectory of simulation results from the benchmark and optimization results indicated that the suggested stepwise optimization method enables a coefficient tuning in a mathematical way.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.1
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• pp.76-83
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• 2016

The various model tests are carried out to estimate and verify a ship performance in the design stage. But in view of the cost, the model test should be applied to every project vessel is very inefficient. Therefore, other methods of predicting the maneuverability with confined data are required at the initial design stage. The purpose of this study is to estimate the hydrodynamic derivatives by using the multiple regression analysis and PMM test data. The characteristics of the stern shape which has an important effect on the maneuverability are applied to the regression analysis in this study. The correlation analysis is performed to select the proper hull form coefficients and stern shape factors used as the variables in the regression analysis. The comparative analysis of estimate results and model test results is conducted on two ships to investigate the effectiveness of the maneuvering hydrodynamic derivatives estimation applied the stern shape. Through the present study, it is verified that the estimation using the stern shape factors as the variables are valid when the stern shape factors are located in the center of the database.

• Journal of Ocean Engineering and Technology
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• v.20 no.6 s.73
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• pp.24-34
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• 2006

Hydrodynamic coefficients strongly affect the dynamic performance of an AUV. Thus, it is important to know the true values of these coefficients, in order to accurately simulate the AUV's dynamic performance. Although these coefficients are generally obtained experimentally, such as through the PMM test, the measured values are not completely reliable because of experimental difficulties and errors. Another approach, by which these coefficients can be obtained, is the observer method, in which a model-based estimation algorithm estimates the coefficients. In this paper, the hydrodynamic coefficients are estimated using two nonlinear observers: a sliding mode observer and an extended Kalman filter. Their performances are evaluated in Matlab simulations, by comparing the estimated coefficients obtained from the two observer methods, with the experimental values as determined from the PMM test. A sliding mode controller is constructed for the diving and steering maneuver by using the estimated coefficients. It is demonstrated that the controller, applied with the estimated values, maintains the desired depth and path with sufficient accuracy.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.1-10
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• 2020

This paper investigates the influence of the Circulating Water Channel (CWC) side wall and support struts on the hydrodynamic coefficient prediction for Autonomous Underwater Vehicles (AUVs) experiments. Computational Fluid Dynamics (CFD) method has been used to model the CWC tests. The hydrodynamic coefficients estimated by CFD are compared with the prediction of experiments to verify the accuracy of simulations. In order to study the effect of side wall on the hydrodynamic characteristics of the AUV in full scale captive model tests, this paper uses the CWC non-dimensional width parameters to quantify the correlation between the CWC width and hydrodynamic coefficients of the chosen model. The result shows that the hydrodynamic coefficients tend to be constant with the CWC width parameters increasing. Moreover, the side wall has a greater effect than the struts.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.201-204
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• 2002

This paper describes the hydrodynamic characteristics of a test-bed AUV SNUUV-I constructed at Seoul National University. The main purpose of the AUV is to carry out fundamental control and hydrodynamic experiments. Its configuration is basically a long cylinder of 1.35m in length and 0.25m in diameter with delta-type wings near its rear end. On the edge of each wing, a thruster of 1/4HP is mounted, which is used for both drive and turn the vehicle for horizontal movement as the output control power is varied. A pair of control surfaces installed near its font part generates pitch moments for vertical movement. The 6 DOF mathematical model of SNUUV-I contains hydrodynamic forces and moments expressed in terms of a set of hydrodynamic coefficients. These coefficients can be classified into linear damping coefficients, linear inertial coefficients and nonlinear damping coefficients. It is important to estimate the exact value of these coefficients to control the vehicle precisely. Among these, the linear coefficients are known to affect the motion of the vehicle dominantly. The linear damping coefficients are estimated by using Extended Kalman Filter. The responses of the vehicle to input signals are used to estimate the hydrodynamic coefficients, which can be inferred from output signals measured from an IMU (inertial motion unit) sensor, while the linear inertial coefficients are calculated by a potential code. By using these coefficients estimated as described above, a simulation program is constructed using Matlab.