• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2108-2116
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• 2008

The paper concerns Fuzzy C-Means clustering based Radial Basis Function neural networks (FCM-RBFNN) and the optimization of the network is carried out by means of Particle Swarm Optimization(PSO). FCM-RBFNN is the extended architecture of Radial Basis Function Neural Network(RBFNN). In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values directly rely on the computation of the relevant distance between data points by means of FCM. Also, as the consequent part of fuzzy rules extracted by the FCM - RBFNN model, the order of four types of polynomials can be considered such as constant, linear, quadratic and modified quadratic. Weighted Least Square Estimator(WLSE) are used to estimates the coefficients of polynomial. Since the performance of FCM-RBFNN is affected by some parameters of FCM-RBFNN such as a specific subset of input variables, fuzzification coefficient of FCM, the number of rules and the order of polynomials of consequent part of fuzzy rule, we need the structural as well as parametric optimization of the network. In this study, the PSO is exploited to carry out the structural as well as parametric optimization of FCM-RBFNN. Moreover The proposed model is demonstrated with the use of numerical example and gas furnace data set.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.11-18
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• 2003

The parametric approaches to sliding mode design are newly proposed for the class of multivariable systems. Our approach is based on an explicit formula for representing all the slid-ing modes using the Lyapunov matrices of full order. By manipulating Lyapunov matrices, the sliding modes which satisfy the design criteria such as the quadratic performance optimization and robust stability to parametric uncertainty, etc., can be easily obtained. The proposed ap-proach enables us to adopt a variety of Lyapunov- (or Riccati-) based approaches to the sliding mode design. Applications to the quadratic performance optimization problem, uncertain systems, systems with uncertain state delay, and the pole-clustering problem are discussed.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.3
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• pp.250-258
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• 2018

Free Standing Hybrid Riser (FSHR) is comprised of vertical steel risers and Flexible Jumpers (FJ). They are jointly connected to a submerged Buoyancy Can (BC). There are several factors that have influence on the behavior of FSHR such as the span distance between an offshore platform and a foundation, BC up-lift force, BC submerged location and FJ length. An optimization method through a parametric study is presented. Firstly, descriptions for the overall arrangement and characteristics of FSHR are introduced. Secondly, a flowchart for optimization of FSHR is suggested. Following that, it is described how to select reasonable ranges for a parametric study and determine each of optimal configuration options. Lastly, numerical analysis based on this procedure is performed through a case study. In conclusion, the relation among those parameters is analyzed and non-dimensional parametric ranges on optimal arrangements are suggested. Additionally, strength analysis is performed with variation in the configuration.

• Journal of Aerospace System Engineering
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• v.8 no.4
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• pp.18-23
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• 2014

In preliminary design phase, the wing geometry of the civil aircraft was determined using the empirical equation and historical data. To make wing geometry more aerodynamically efficient, an aerodynamic shape optimization was conducted. For this purpose the parametric modeling, high fidelity CFD analysis and metamodel-based optimal design technique were adopted. The parametric modeling got the design process to achieve the improvement by generating the configuration outputs easily for the major design variables. The optimal design equations were formularized as the type of the multi-objective functions considering low/high speed and lift/drag coefficient. The optimal solution was explored with the help of the kriging metamodel and the desirability function, therefore the optimal wing planform was sought to be excellent at both low and high speed region. Additionally the optimal wing planform was validated that it was excellent not only at the specific AOA, but also all over the range of AOA.

• The Journal of Korea Robotics Society
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• v.12 no.1
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• pp.19-25
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• 2017

A design methodology for parametric design optimization of washing machine door is presented. We develop a motion simulator and a robotic door to simulate the various motion of washing machine doors. The motion of the washing machine door is related to hinge parameters. Springs and dampers are usually used in the hinge of washing machine door for controlling motion of the door. A physical simulator of the door motion is used for finding candidate parameters of the hinge and a robotic door whose motion is controlled algorithmically is used for consumer tests. Through the consumer evaluation on the robotic motion, the optimized parameters are determined. We find the optimal parameters as a function of angle and angular velocity of the door.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.569-570
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• 2007

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.269-273
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• 2003

We consider an efficient parametric estimation method of spatial dependence in weak stationary processes. Spatial dependence is modeled through variogram and correlogram. Most of parametric estimation methods of correlogram use two step method; nonparametric estimation and parametric integration. We bind these two steps into one step by using GEE method instead of least squares type optimization. Our one step method is more efficient statistically and gives a clear interpretation of related concepts used in traditional two step methods.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.159-165
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• 2005

This paper designs observers for matrix second-order linear systems on the basis of generalized eigenstructure assignment via unified parametric approach. It is shown that the problem is closely related with a type of so-called generalized matrix second-order Sylvester matrix equations. Through establishing two general parametric solutions to this type of matrix equations, two unified complete parametric methods for the proposed observer design problem are presented. Both methods give simple complete parametric expressions for the observer gain matrices. The first one mainly depends on a series of singular value decompositions, and is thus numerically simple and reliable; the second one utilizes the right factorization of the system, and allows eigenvalues of the error system to be set undetermined and sought via certain optimization procedures. A spring-mass system is utilized to show the effect of the proposed approaches.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.565-571
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• 2001

As a method of structural optimization, a practical algorithm based on the Taguchi method is developed. The Taguchi method is applied iteratively updating the level values of design variables. The design region is translated or reduced during optimization and by appropriate choice of reduction factor and initial level intervals, a near-optimum solution can be found very efficiently. To treat inequality constraints, a variable penalty method is utilized. A software system named 'DS/Taguchi' is developed by integrating the proposed algorithm and commercial finite element analysis codes on the parametric CAD platform. Two examples are taken to examine the performance of the proposed algorithm and the developed software system.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.180-187
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• 2003

A CAD-based seamless design system for MEMS named DS/MEMS was developed which performs coupled-field analysis, optimal and robust design. DS/MEMS has been developed by means of integrating commercial codes and inhouse code-SolidWorks, FEMAP, ANSYS and CA/MEMS. This strategy results in versatility that means to include various analysis model, corresponding analyses and approximated design sensitivity analysis and user friendliness that design variables are taken to be selectable directly from a CAD model, that the problem is formulated under a window environment and that the manual job during optimization process is almost eliminated. DS/MEMS works on a parametric CAD platform, integrating CAD modeling, analysis, and optimization. Nonlinear programming algorithms, the Taguchi method, and response surface method are made available for optimization. One application problem is taken to illustrate the proposed methodology and show the feasibility of DS/MEMS as a practical tool.