• Title/Summary/Keyword: Performance parameter

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Analysis of Nonlinear Control Characteristic for the Parameter Variation of Vector Control-Fed Induction Motors (벡터제어-구동 유도전동기의 파라미터 변동에 대한 비선형 제어특성의 해석)

  • Shon, Jin-Geun;Suk, Won-Yeob;Song, Yang-Hoi;Jeon, Hee-Jong
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.53 no.2
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    • pp.51-57
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    • 2004
  • Vector control schemes are used in inverter-fed induction motor drives to obtain high performance. Crucial to the success of the vector control scheme is the knowledge of the instantaneous position of the rotor flux. However, the position of the rotor flux change with temperature and magnetic saturation of the motor. This variation cause deterioration of both steady state and dynamic operation of the motor drives. Performance degradation is in the form of input-output torque nonlinearity and saturation of the motor. Analytic expressions are derived to evaluate the effects due to parameter sensitivity. Also, dynamic response is shown by speed command with the variation of stator and rotor resistance.

An alternative method for estimating lognormal means

  • Kwon, Yeil
    • Communications for Statistical Applications and Methods
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    • v.28 no.4
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    • pp.351-368
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    • 2021
  • For a probabilistic model with positively skewed data, a lognormal distribution is one of the key distributions that play a critical role. Several lognormal models can be found in various areas, such as medical science, engineering, and finance. In this paper, we propose a new estimator for a lognormal mean and depict the performance of the proposed estimator in terms of the relative mean squared error (RMSE) compared with Shen's estimator (Shen et al., 2006), which is considered the best estimator among the existing methods. The proposed estimator includes a tuning parameter. By finding the optimal value of the tuning parameter, we can improve the average performance of the proposed estimator over the typical range of σ2. The bias reduction of the proposed estimator tends to exceed the increased variance, and it results in a smaller RMSE than Shen's estimator. A numerical study reveals that the proposed estimator has performance comparable with Shen's estimator when σ2 is small and exhibits a meaningful decrease in the RMSE under moderate and large σ2 values.

Sweet Area Determination by Performance Sensitivity Analysis for an Automotive Vehicle Suspension (자동차용 현가장치의 성능감도해석에 의한 안정승차영역의 결정)

  • Park, Ho;Hahn, Chang-Su;Kim, Byeong-Woo;Kim, Dong-Gyu
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.12 no.1
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    • pp.92-100
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    • 2003
  • Using a quarter car model, an analytic method for performance estimation of a vehicle suspension system with respect to frequency response, RMS response and performance index is presented. From frequency response function, compromization of response performance to the whole frequency range is verified and from RMS response and performance index, sensitivity of ride md handling characteristics are examined. Using a full car model, sweet area(stable ride area) are determined and performance sensitivity is estimated according to the change of feedback gains. In order to esimate the output sensitivity, response we is displayed using a 3-dimensional contour plot. Design data n suggested for optimal design parameter esimation, which maximize the performance of the given suspension system.

FAST ONE-PARAMETER RELAXATION METHOD WITH A SCALED PRECONDITIONER FOR SADDLE POINT PROBLEMS

  • OH, SEYOUNG;YUN, JAE HEON
    • Journal of applied mathematics & informatics
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    • v.34 no.1_2
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    • pp.85-94
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    • 2016
  • In this paper, we first propose a fast one-parameter relaxation (FOPR) method with a scaled preconditioner for solving the saddle point problems, and then we present a formula for finding its optimal parameter. To evaluate the effectiveness of the proposed FOPR method with a scaled preconditioner, numerical experiments are provided by comparing its performance with the existing one or two parameter relaxation methods with optimal parameters such as the SOR-like, the GSOR and the GSSOR methods.

A Parameter Optimization Algorithm for Power System Stabilization (전력 계통 안정화를 위한 선재설계에 관한 연구)

  • 곽노홍;문영현
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.8
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    • pp.792-804
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    • 1990
  • This paper describes an efficient optimization algorithm by calculating sensitivity function for power system stabilization. In power system, the dynamic performance of exciter, governor etc. following a disturbance can be presented by a nonlinear differential equation. Since a nonlinear equation can be linearized for small disturbances, the state equation is expressed by a system matrix with system parameters. The objective function for power system operation will be related to the system parameter and the initial state at the optimal control condition for control or stabilization. The object function sensitivity to the system parameter can be considered to be effective in selecting the optimal parameter of the system.

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A. Study on Power System Stabilization by using Parameter Optimization (최적 파라미터를 이용한 전력계통 안정화에 관한 연구)

  • Moon, Young-Hyun;Kwak, No-Hong
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.179-183
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    • 1989
  • This study presents a methodology to choose the optimal parameter of controller by using the performance index sensitivity. The pro-posed method is to select the controller parameter to have the minimum sensitivity. It is shown that the optimal parameter proves the effectiveness in the dynamic stability of power system.

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Robust Parameter Design for Multiple Quality Characteristics using Factor Analysis

  • Kwon, Yong-Man;Chang, Duk-Joon
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.04a
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    • pp.131-139
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    • 2004
  • Robust parameter design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper, we introduce a factor analysis approach to simultaneously optimize multiple quality characteristics in the robust parameter design. An example is illustrated to compare it with already proposed method.

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Determination and Analysis of Signal-to-Noise Ratios for Parameter Design with Dynamic Characteristics (동특성 파라미터설계를 위한 SN비의 결정 및 분석)

  • 김성준
    • Journal of Korean Society for Quality Management
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    • v.26 no.2
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    • pp.17-26
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    • 1998
  • Taguchi's parameter design is a method for quality improvement by making the performance fo a system robust to noise. Parameter design with dynamic characteristics has been recently the subject of much interest. This paper is concerned with a review and a generalization of the Signal-to-Noise (SN) ratio, a quality measure for parameter design with dynamic characteristics, proposed by Taguchi. We present a method for determination and analysis of the generalized SN ratio and illustrate its implementation by example.

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A Study on the SNR Estimation Performance of Hierarchical 16QAM (계층 16QAM의 SNR 추정 성능에 대한 연구)

  • Kwak, Jae-Min
    • Journal of Advanced Navigation Technology
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    • v.16 no.6
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    • pp.975-981
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    • 2012
  • The SNR estimation performance of hierarchical 16QAM system, which is adopted to simultaneous transmission or efficient image transmission system, is analyzed. Hierarchical 16QAM is modulation system which has different constellation shape from conventional QAM and can provide users with high quality and low quality of data services simultaneously by controlling hierarchical modulation parameter. Assuming AWGN channel, SNR estimation performance characteristics are investigated considering hierarchical modulation parameter and type of constellation points. From simulation results, it is found that constellation point showing superior SNR estimation performance relative to other points is exist. Also, it is known that according to hierarchical modulation parameter, SNR estimation range with more accurate estimation performance is divided.

Robust Feature Parameter for Implementation of Speech Recognizer Using Support Vector Machines (SVM음성인식기 구현을 위한 강인한 특징 파라메터)

  • 김창근;박정원;허강인
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.3
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    • pp.195-200
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    • 2004
  • In this paper we propose effective speech recognizer through two recognition experiments. In general, SVM is classification method which classify two class set by finding voluntary nonlinear boundary in vector space and possesses high classification performance under few training data number. In this paper we compare recognition performance of HMM and SVM at training data number and investigate recognition performance of each feature parameter while changing feature space of MFCC using Independent Component Analysis(ICA) and Principal Component Analysis(PCA). As a result of experiment, recognition performance of SVM is better than 1:.um under few training data number, and feature parameter by ICA showed the highest recognition performance because of superior linear classification.