• Title/Summary/Keyword: Error synthesis model

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Development of A Validation System For Automatic Radiopharmaceutical Synthesis Process Using Network Modeling (방사성의약품 합성 프로세스 검증을 위한 네트워크 모델링)

  • Lee, Cheol-Soo;Heo, Eun-Young;Kim, Jong-Min;Kim, Dong-Soo
    • IE interfaces
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    • v.24 no.3
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    • pp.187-195
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    • 2011
  • The automatic radiopharmaceutical module consists of several 2-way valves, couple of syringes, gas supply unit, heating(cooling) unit and sensors to control the chemical reagents as well as to help the chemical reaction. In order to control the actuators of radiopharmaceutical module, the process is tabulated using spread sheet as like excel. Unlike the common program, a trivial error is too critical to allowed in the process because the error can lead to leak the radioactive reagent and to cause the synthesis equipment failure during synthesizing. Hence, the synthesis process has been validated using graphic simulation while the operator checks the whole process visually and undergoes trial and error. The verification of the synthesis process takes a long time and has a difficulty in finding the error. This study presents a methodology to verify the process algebraically while the radiopharmaceutical module is converted to the network model. The proposed method is validated using actual synthesis process.

Model Reference Adaptive Control for Linear System with Improved Convergence Rate -SIGNAL SYNTHESIS METHOD- (선형시스템을 위한 개선된수렴속도를 갖는 기준모델 적응제어기- SYNTHESIS METHOD)

  • Lim, Kye-Young
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.37 no.10
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    • pp.733-739
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    • 1988
  • Adaptive controllers for linear system whose nominal values of coefficients only are known, that is corrupted by disturbance, are designed by signal synthesis model reference adaptive control (MRAC). This design is stemmed from the Lyapunov direct method. To reduce the model following error and to improve the conrergence rate of the design, an indirect suboptimal control law is de rived using the Hamilton Jacobi Beellman equation. Proper compensaton for the effects of time varying coefficients and plant disturbance are suggested. In the design procedure no complete identification of unknown coefficients are required.

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TSK Fuzzy Model Based Hybrid Adaptive Control of Nonlinear Systems (비선형 시스템의 TSK 퍼지모델 기반 하이브리드 적응제어)

  • Kim, You-Keun;Kim, Jae-Hun;Hyun, Chang-Ho;Kim, Eun-Tai;Park, Mi-Gnon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.211-216
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    • 2004
  • In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

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A Generalized Volumetric Error Modeling Considering Backlash in Machine Tools (방향성을 고려한 일반화된 공작기계의 입체오차 모델링)

  • Ahn, Kyoung-Gee;Cho, Dong-Woo
    • Journal of the Korean Society for Precision Engineering
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    • v.19 no.4
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    • pp.124-131
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    • 2002
  • In this paper, an extended volumetric error model considering backlash in a three-axis machine tool was proposed and utilized for calculating the volumetric error of the machine tool at any position in three-dimensional workspace. Backlashes are interrelated; i.e. the angular backlash affects the straightness errors which then affect talc calculated squareness errors. Therefore, a new concept was introduced to define the backlash of squareness errors to incorporate the backlash of squareness error into the volumetric error, and the characteristics of the backlash of squareness error were investigated. The effects of backlash errors were assessed, by experiments. for 21 geometric errors of a machine tool. The backlash error was shown to be one of the systematic errors of a machine tool. And a generalized volumetric error model formulator for three-axis machine tools was developed, which allowed us to formulate machine tool synthesis error models far all possible machine tool configurations only with machine tool topology information. Based on these volumetric error model and model formulator, a computer-aided volumetric error analysis system was developed for a three-axis machine tool in this paper. Then the volumetric error at an arbitrary position can be obtained, and displayed in a three-dimensional graphic form.

Variance components for two-way nested design data

  • Choi, Jaesung
    • Communications for Statistical Applications and Methods
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    • v.25 no.3
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    • pp.275-282
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    • 2018
  • This paper discusses the use of projections for the sums of squares in the analyses of variance for two-way nested design data. The model for this data is assumed to only have random effects. Two different sizes of experimental units are required for a given experimental situation, since nesting is assumed to occur both in the treatment structure and in the design structure. So, variance components are coming from the sources of random effects of treatment factors and error terms in different sizes of experimental units. The model for this type of experimental situation is a random effects model with more than one error terms and therefore estimation of variance components are concerned. A projection method is used for the calculation of sums of squares due to random components. Squared distances of projections instead of using the usual reductions in sums of squares that show how to use projections to estimate the variance components associated with the random components in the assumed model. Expectations of quadratic forms are obtained by the Hartley's synthesis as a means of calculation.