• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.3
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• pp.154-163
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• 2013

In this paper, we propose a formation control algorithm for underactuated autonomous underwater vehicles (AUVs) with parametric uncertainties using the approach angle. The approach angle is used to solve the underactuated problem for AUVs, and the leader-follower strategy is used for the formation control. The proposed controller considers the nonzero off-diagonal terms of the mass matrix of the AUV model and the associated parametric uncertainties. Using the state transformation, the mass matrix, which has nonzero off-diagonal terms, is transformed into a diagonal matrix to simplify designing the control. To deal with the parametric uncertainties of the AUV model, a self-recurrent wavelet neural network is used. The proposed formation controller is designed based on the dynamic surface control technique. Some simulation results are presented to demonstrate the performance of the proposed control method.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.711-722
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• 2020

An optimization framework using genetic algorithms has been developed towards an automated parametric optimization of the Octabuoy semi-submersible design. Compared with deep draft production units, the design of the shallow draught Octabuoy semi-submersible provides a floating system with improved motion characteristics, being less susceptible to vortex induced motions in loop currents. The relatively large water plane area results in a decreased natural heave period, which locates the floater in the wave period range with more wave energy. Considering this, the hull design of Octabuoy semi-submersible has been optimized to improve the floater's motion performance. The optimization has been conducted with optimized parameters of the pontoon's rectangular cross section area, the cone shaped section's height and diameter. Through numerical evaluations of both the 1st-order and 2nd-order hydrodynamics, the optimization through genetic algorithms has been proven to provide improved hydrodynamic performance, in terms of heave and pitch motions. This work presents a meaningful framework as a reference in the process of floating system's design.

• Communications of the Korean Mathematical Society
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• v.36 no.1
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• pp.103-119
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• 2021

In this article, we study a system of generalized set-valued parametric ordered variational inclusion problems with operator ⊕ in ordered Banach spaces. We introduce the concept of the resolvent operator associated with (α, λ)-ANODSM set-valued mapping and establish the existence theorem of solution for the system of generalized set-valued parametric ordered variational inclusion problems in ordered Banach spaces. In order to prove the existence of solution, we suggest an iterative algorithm and discuss the convergence analysis under some suitable mild conditions.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.641-653
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• 2022

Penalized least squares methods are important tools to simultaneously select variables and estimate parameters in linear regression. The penalized maximum likelihood can also be used for the same purpose assuming that the error distribution falls in a certain parametric family of distributions. However, the use of a certain parametric family can suffer a misspecification problem which undermines the estimation accuracy. To give sufficient flexibility to the error distribution, we propose to use the symmetric log-concave error distribution with LASSO penalty. A feasible algorithm to estimate both nonparametric and parametric components in the proposed model is provided. Some numerical studies are also presented showing that the proposed method produces more efficient estimators than some existing methods with similar variable selection performance.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.6
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• pp.43-49
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• 2001

A reduced machining time and increased accuracy for the sculptured surface are very important when producing complicated parts. The step-size and tool-path interval are essential components in high speed and high resolution machining. If they are small, the machining time will increase, whereas if they are large, rough surfaces will be caused. In particular, the machining time, which is key in high speed machining, is affected by the tool-path interval more than the step-size. The conventional method for calculating the tool=path interval is to select a small parametric increment of a small increment based on the curvature of the surface. However, this approach also has limitations. The first is that the tool-path interval can not be calculated precisely. The second is that a separate tool-path interval needs to be calculated in each of the three cases. The third is that the conversion from Cartesian domain to parametric domain or vice versa must be necessary. Accordingly, the current study proposes a new tool-path interval algorithm that do not involve a curvature and that is not necessary for any conversion and a variable step-size algorithm for NURBS.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.4 s.235
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• pp.570-577
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• 2005

In this study a complete 3D surface reconstruction method is proposed based on the concept that the vertices of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.931-938
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• 2008

In this paper, a novel localization algorithm robust to the unmodeled systematic odometry errors is proposed for low-cost non-holonomic mobile robots. It is well known that the most pose estimators using odometry measurements cannot avoid the performance degradation due to the dead-reckoning of systematic odometry errors. As a remedy for this problem, we tty to reflect the wheelbase error in the robot motion model as a parametric uncertainty. Applying the Krein space estimation theory for the discrete-time uncertain nonlinear motion model results in the extended robust Kalman filter. This idea comes from the fact that systematic odometry errors might be regarded as the parametric uncertainties satisfying the sum quadratic constrains (SQCs). The advantage of the proposed methodology is that it has the same recursive structure as the conventional extended Kalman filter, which makes our scheme suitable for real-time applications. Moreover, it guarantees the satisfactoty localization performance even in the presence of wheelbase uncertainty which is hard to model or estimate but often arises from real driving environments. The computer simulations will be given to demonstrate the robustness of the suggested localization algorithm.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.11 no.2
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• pp.31-39
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• 2015

Pipe wall-thinning by flow-accelerated corrosion (FAC) and various types of erosion is a significant and costly damage phenomenon in secondary piping systems of nuclear power plants (NPPs). Most NPPs have management programs to ensure pipe integrity due to wall-thinning that includes periodic measurements for pipe wall thicknesses using ultrasonic tests (UTs). Nevertheless, thinning evaluations are not easy because the amount of thickness reduction being measured is often quite small compared to the accuracy of the inspection technique. U.S. Electric Power Research Institute (EPRI) had proposed Total Point Method (TPM) as a thinning occurrence evaluation method, which is a very useful method for detecting locally thinned pipes or fittings. However, evaluation engineers have to discern manually the measurement data because there are no numerical algorithm for TPM. In this study, numerical algorithms were developed based on non-parametric and parametric statistical method.

• Journal of KIBIM
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• v.5 no.4
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• pp.11-22
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• 2015

Government efforts for green growth policy initiatives demand low-carbon technologies in the road construction industry. The purpose of this paper is to develop an algorithm of a road alignment design solution for establishing the multi-dimensional information, and to calculate carbon emission quantity due to the geometric design elements in the planning phase of road alignment. The paper developed a calculation method for carbon emission quantity by drawing a speed profile reflected in the operating speed, acceleration and deceleration, which are majors factor of carbon emissions while driving and by applying a carbon emission factor. From this effort, it enabled alignment planning to reduce carbon emission. Object-based parametric design methods of the cross-sections were proposed for alignment planning, and the paper demonstrated a BIM-based road alignment planning solution. The proposed solutions can provide multi-dimensional information on carbon emission quantity and cross section elements through driving simulation. It is expected to allow construction of eco-friendly roads by deriving optimal road alignment to minimize environmental costs.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1561-1570
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• 1997

This study explores the treatment of the max-value cost function over a parameter interval in parametric optimization. To avoid the computational burden of the transformation treatment using an artificial variable, a direct treatment of the original max-value cost function is proposed. It is theoretically shown that the transformation treatment results in demanding an additional equality constraint of dual variables as a part of the Kuhn-Tucker necessary conditions. Also, it is demonstrated that the usability and feasibility conditions on the search direction of the transformation treatment retard convergence rate. To investigate numerical performances of both treatments, typical optimization algorithms in ADS are employed to solve a min-max steady-state response optimization. All the algorithm tested reveal that the suggested direct treatment is more efficient and stable than the transformation treatment. Also, the better performing of the direct treatment over the transformation treatment is clearly shown by constrasting the convergence paths in the design space of the sample problem. Six min-max transient response optimization problems are also solved by using both treatments, and the comparisons of the results confirm that the performances of the direct treatment is better than those of the tranformation treatment.