• Title/Summary/Keyword: parameter function

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Notes on Parametric Estimations in a Power Function Distribution

  • Woo, Jungsoo;Yoon, Gi-Ern
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.919-928
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    • 1999
  • We shall propose the MME MLE and UMVUE for the mean parameter and the right-tail probability in a power function distribution and obtain the mean squared errors for the proposed estimators. And we shall compare numerically efficiencies of the MME MLE and UMVUE of the mean parameter and the right-tail probability in a power function distribution.

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The Parameter Estimation of DC-DC Converter by System Identification Method (시스템 식별 기법을 이용한 DC-DC 컨버터 파라메터 추정)

  • Jeon, Jin-Hong;Kim, Tae-Jin;Kim, Kwang-Su;Kim, Kwang-Hwa
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.503-506
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    • 2003
  • In this paper, we present the results of parameter estimation for do-dc converter model by system identification. The parameter estimation for dc-dc converter aims at the diagnosis of its operating status. we applied the system identification method for parameter estimation. For verification of estimated parameter, we compare bode plot of estimated system transfer function and measurement results of HP4194 instrument.

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Parameter Extraction Procedure for Ion Implantation Profiles to Establish Robust Database based on Tail Function

  • Suzuki, Kunihiro;Kojima, Shuichi
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.10 no.4
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    • pp.251-259
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    • 2010
  • We proposed a tail function parameter extraction procedure for the establishment of a robust ion implantation database. We showed that, for the expression of ion implantation profiles, there are many local minimum values set for the third and fourth moment parameters of $\gamma$ and $\beta$ for the Pearson function that comprises the standard dual Pearson and tail functions. We proposed the use of a joined tail function as a mediate function to extract $\gamma$ and $\beta$, and demonstrated that this enables us to extract the parameters uniquely. Other parameters associated with channeling phenomena can also be simply and uniquely extracted by our procedure.

Estimations of the skew parameter in a skewed double power function distribution

  • Kang, Jun-Ho;Lee, Chang-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.4
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    • pp.901-909
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    • 2013
  • A skewed double power function distribution is defined by a double power function distribution. We shall evaluate the coefficient of the skewness of a skewed double power function distribution. We shall obtain an approximate maximum likelihood estimator (MLE) and a moment estimator (MME) of the skew parameter in the skewed double power function distribution, and compare simulated mean squared errors for those estimators. And we shall compare simulated MSEs of two proposed reliability estimators in two independent skewed double power function distributions with different skew parameters.

A Comparison of Parameter Design Methods for Multiple Performance Characteristics (다특성 파라미터설계 방법의 비교 연구)

  • Soh, Woo-Jin;Yum, Bong-Jin
    • Journal of Korean Institute of Industrial Engineers
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    • v.38 no.3
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    • pp.198-207
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    • 2012
  • In product or process parameter design, the case of multiple performance characteristics appears more commonly than that of a single characteristic. Numerous methods have been developed to deal with such multi-characteristic parameter design (MCPD) problems. Among these, this paper considers three representative methods, which are respectively based on the desirability function (DF), grey relational analysis (GRA), and principal component analysis (PCA). These three methods are then used to solve the MCPD problems in ten case studies reported in the literature. The performance of each method is evaluated for various combinations of its algorithmic parameters and alternatives. Relative performances of the three methods are then compared in terms of the significance of a design parameter and the overall performance value corresponding to the compromise optimal design condition identified by each method. Although no method is significantly inferior to others for the data sets considered, the GRA-based and PCA-based methods perform slightly better than the DF-based method. Besides, for the PCA-based method, the compromise optimal design condition depends much on which alternative is adopted while, for the GRA-based method, it is almost independent of the algorithmic parameter, and therefore, the difficulty involved in selecting an appropriate algorithmic parameter value can be alleviated.

A Novel Sensorless Low Speed Vector Control for Synchronous Reluctance Motors Using a Block Pulse Function-Based Parameter Identification

  • Ahmad Ghaderi;Tsuyoshi Hanamoto;Teruo Tsuji
    • Journal of Power Electronics
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    • v.6 no.3
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    • pp.235-244
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    • 2006
  • Recently, speed sensorless vector control for synchronous reluctance motors (SYRMs) has deserved attention because of its advantages. Although rotor angle calculation using flux estimation is a straightforward approach, the DC offset can cause an increasing pure integrator error in this estimator. In addition, this method is affected by parameter fluctuation. In this paper, to control the motor at the low speed region, a modified programmable cascaded low pass filter (MPCPLF) with sensorless online parameter identification based on a block pulse function is proposed. The use of the MPCLPF is suggested because in programmable, cascade low pass filters (PCLPF), which previously have been applied to induction motors, the drift increases vastly wl)en motor speed decreases. Parameter identification is also used because it does not depend on estimation accuracy and can solve parameter fluctuation effects. Thus, sensorless speed control in the low speed region is possible. The experimental system includes a PC-based control with real time Linux and an ALTERA Complex Programmable Logic Device (CPLD), to acquire data from sensors and to send commands to the system. The experimental results show the proposed method performs well, speed and angle estimation are correct. Also, parameter identification and sensorless vector control are achieved at low speed, as well as, as at high speed.

Output-only modal parameter identification for force-embedded acceleration data in the presence of harmonic and white noise excitations

  • Ku, C.J.;Tamura, Y.;Yoshida, A.;Miyake, K.;Chou, L.S.
    • Wind and Structures
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    • v.16 no.2
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    • pp.157-178
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    • 2013
  • Output-only modal parameter identification is based on the assumption that external forces on a linear structure are white noise. However, harmonic excitations are also often present in real structural vibrations. In particular, it has been realized that the use of forced acceleration responses without knowledge of external forces can pose a problem in the modal parameter identification, because an external force is imparted to its impulse acceleration response function. This paper provides a three-stage identification procedure as a solution to the problem of harmonic and white noise excitations in the acceleration responses of a linear dynamic system. This procedure combines the uses of the mode indicator function, the complex mode indication function, the enhanced frequency response function, an iterative rational fraction polynomial method and mode shape inspection for the correlation-related functions of the force-embedded acceleration responses. The procedure is verified via numerical simulation of a five-floor shear building and a two-dimensional frame and also applied to ambient vibration data of a large-span roof structure. Results show that the modal parameters of these dynamic systems can be satisfactorily identified under the requirement of wide separation between vibration modes and harmonic excitations.

Error Reduction of Sliding Mode Control Using Sigmoid-Type Nonlinear Interpolation in the Boundary Layer

  • Kim, Yoo-K.;Jeon, Gi-J.
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1810-1815
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    • 2003
  • Sliding mode control with nonlinear interpolation in the boundary layer is proposed. A modified sigmoid function is used for nonlinear interpolation in the boundary layer and its parameter is tuned by a fuzzy logic controller. The fuzzy logic controller that takes the distance between the system state and the sliding surface as its input guides the choice of parameter of the modified sigmoid function and the parameter is on-line tuned. Owing to the decreased thickness, the proposed method has better tracking performance than the conventional linear interpolation method. To demonstrate its performance, the proposed control algorithm is applied to a simple nonlinear system model.

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Output feedback model predictive control for Wiener model with parameter dependent Lyapunov function

  • Yoo, Woo-Jong;Ji, Dae-Hyun;Lee, Sang-Moon;Won, Sang-Chul
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.685-689
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    • 2005
  • In this paper, we consider a robust output feedback model predictive controller(MPC) design for Wiener model. Nonlinearities that couldn't be represented in static nonlinearity block of Wiener model are regarded as uncertainties in linear block. An dynamic output feedback controller design method is presented for Wiener MPC. According to MPC algorithm, the control law is computed based on linear matrix inequality(LMI)at each sampling time by solving convex optimization. Also, a new parameter dependent Lyapunov function is proposed to get a less conservative condition. The results are illustrated with numerical example.

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The Design of Model Reference Adaptive Controller via Block Pulse Functions (블럭펄스 함수를 이용한 기준 모델 적응 제어기 설계)

  • Kim, Jin-Tae;Kim, Tai-Hoon;Lee, Myung-Kyu;Ahn, Doo-Soo
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.51 no.1
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    • pp.1-7
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    • 2002
  • This paper proposes a algebraic parameter determination of MRA(Model Reference Adaptive Control) controller using block Pulse functions and block Pulse function's differential operation. Generally, adaption is performed by solving differential equations which describe adaptive low for updating controller parameter. The proposes algorithm transforms differential equations into algebraic equation, which can be solved much more easily inn a recursive manner. We believe that proposes methods are very attractive and proper for parameter estimation of MRAC controller on account of its simplicity and computational convergence.