• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1549-1557
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• 2018

Optimizing the design of large-scale electric machines based on nonlinear finite element analysis (FEA) requires longer computation time than other applications of FEA, mainly due to the huge size of the machines. This paper addresses a new region decision method (RDM) with mesh adaptive direct search (MADS) for the optimal design of wind generators in order to reduce the computation time. The validity of the proposed algorithm is evaluated using Rastrigin and Goldstein-Price benchmark function. Moreover, the algorithm is employed for the optimal design of a 5.6MW interior permanent magnet synchronous generator to minimize the torque ripple. Additionally, mechanical stress analysis as well as electromagnetic field analysis have been implemented to prevent breakdown caused by large centrifugal forces of the modified design.

• The Transactions of the Korean Institute of Electrical Engineers
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• 제40권9호
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• pp.929-936
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• 1991

An estimator for a discrete nonlinear system is derived in the sense of minimum mean square error. An optimal estimator for nonlinear system is very difficult to find and it will be infinite dimensional even if it is found. It has been known that the statistical linearization technique makes it possible to obtain a finite dimensional estimator. In this paper, the procedure of its derivation using the statistical linearization technique that gives an exact mean and variance information is introduced in the sense of minimum mean square error. The derived estimator cannot be clainmed to be globally optimal estimator because it uses the Gaussian assumption to the non-Gaussian distributed nonlinear output. However, the proposed filter exhibits a better performance compared to extended Kalman filter. Simulation results of a simple example present the improvement of the proposed filter in convergent property over the extended Kalman filter.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제27권12호
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• pp.2028-2038
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• 2003

High-speed feed drive systems have been widely used in the manufacturing and semiconductor industries. Specifications for high-speed systems require more advanced capabilities than conventional feed drive systems. It is necessary to devise special design concepts to achieve the level of performance for high-speed feed drive systems. In this paper, an integrated design method is proposed for high-speed feed drive systems in which the interactions between mechanical and electrical subsystems ought to be considered simultaneously during the design process. Based on the integrated design method, a nonlinear optimal design procedure of mechanical subsystems considering the Abbe and radius errors is accomplished through the design process of electrical subsystems satisfying the control stability and the saturation condition of actuators as well as the relative stability. Both mechanical and electrical parameters are considered as design variables. Simulations and numerical case studies show that the integrated design method of high-speed feed drive systems creates results satisfying the desired performances of mechatronic systems.

• Magazine of the Korean Society of Agricultural Engineers
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• 제27권4호
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• pp.61-67
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• 1985

This study is concerned with the optimum design of reinforced concrete frame structure with multi-stories and multi-bays by Limit State Design Method aimed to establish a synthetical optimal method that can simultaneously acomplish structural analysis and sectional desig. For optimum solution, the Successive Linear Programming known as effective to nonlinear optimization problem: including both multi-design variables and mulit-constrained condition was applied. The developed algorithm was applied to an actual structure and reached following results. 1)The developed algorithm was rvey effective converging to an optimal solution with 3 to 5 iteration. 2)An optimal solution was showed when bending moment redistribution factor a was 0.80. 3)The column was, regardless of story, controlled by the long column when unbraced, while in case of braced column, it is designed with 3 short column controlled by thrust and bending moment, and the supporting condition had little effect on the optimization results.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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• pp.103-110
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• 2004

Recently, performance based seismic design (PBSD) methods in numerous forms have been suggested and widely studied as a new concept of seismic design. The PBDSs are far from being practical due to complexity of algorithms resided in the design philosophy In this paper, optimal seismic design method based on displacement coefficient method (DCM) described in FEMA 273 is developed. As an optimizer simple genetic algorithms are used for implementations. In the optimization problem formulated in this paper, strength design criteria, stiffness design criteria, and nonlinear response criteria specified in DCM are included in design constraints. The optimal performance based design(OPBD) method is applied to seismic design of a 9-story two-dimensional steel frame structures.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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• pp.636-643
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• 2005

Recently, performance based seismic design (PBSD) methods have been suggested in numerous forms and widely studied as a new concept of seismic design. The PBDSs are far from being practical method due to complexity of algorithms resided in the design philosophy. In this paper, optimal seismic design method based on displacement coefficient method (DCM) described in FEMA 273 is developed. As an optimizer simple genetic algorithms are used for implementations. In the optimization problem formulated in this Paper, strength design criteria stiffness design criteria, and nonlinear response criteria specified in DCM are included in design constraints. The optimal performance based design(OPBD) method is applied to seismic design of a 3-story two-dimensional steel frame structures.

• Journal of the Korean Operations Research and Management Science Society
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• 제13권2호
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• pp.34-46
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• 1988

This paper deals with design problem of unit load automated storage/retrieval systems (AS/RS). We propose an optimal design model in which the investment and maintenance costs of AS/RS, operating under dual command model is minimized over a time horizon satisfying the warehouse dimensional constraints. The model is formulated as an integer nonlinear program and an algorithm is proposed to find an optimum solution. The valididty of the solution algorithm is illustrated through an example.

• Transactions of the Korean Society of Automotive Engineers
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• 제8권5호
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• pp.138-147
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• 2000

Vehicle suspension systems are parts which effect performances of a vehicle such as ride quality, handing characteristics, straight performance and steering effort etc. Kinematic design is a decision of joints` position for straight performance and steering effort. But, when vehicle is rebounding and bumping, chang of joints` displacement is nonlinear and a surmise of straight performance and steering effort at that joints` position is difficult. So design of suspension systems is done through a inefficient method of tried-and-error depending on designer`s experience. In this paper, kinematic design of suspension systems was done through the optimal design using a genetic algorithm. For this optimal design, the function for quantification of straight performance and steering effort was made, and the kinematic design method of suspension systems having this function as the objective function was suggested.

• Proceedings of the KIEE Conference
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.122-125
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• 2000

The paper describes the adaptation of evolutionary fuzzy model ins (EFM) in developing global function approximation tools for use in genetic algorithm based optimization of nonlinear structural systems. EFM is an optimization process to determine the fuzzy membership parameters for constructing global approximation model in a case where the training data are not sufficiently provided or uncertain information is included in design process. The paper presents the performance of EFM in terms of numbers of fuzzy rules and training data, and then explores the EFM based sizing of automotive component for passenger protection.