• 제목/요약/키워드: Process Parameter

검색결과 3,070건 처리시간 0.026초

신경망 외란관측기와 파라미터 보상기를 이용한 PMSM의 속도제어 (Precision Speed Control of PMSM Using Neural Network Disturbance observer and Parameter compensation)

  • 고종선;이용재;김규겸
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2001년도 전력전자학술대회 논문집
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    • pp.389-392
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    • 2001
  • This paper presents neural load disturbance observer that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a neural deadbeat observer. To reduce of the noise effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM (recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. The proposed estimator is combined with a high performance neural torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation, are shown in this paper.

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ON THE SQUARE OF BROWNIAN DENSITY PROCESS

  • Cho, Nhan-Sook
    • 대한수학회지
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    • 제34권3호
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    • pp.707-717
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    • 1997
  • The square of Brownian density process $Q^\lambda$ is defined where $\lambda$ is a parameter. Applying limit theorems of stochastic integrals w.r.t. martingale measure, we prove a weak limit theorem for $Q^\lambda$ in $D_{S'(R^d)}[0,1]$.

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

  • 소우진;염봉진
    • 대한산업공학회지
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    • 제38권3호
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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.

신경망 외란관측기와 파라미터 보상기를 이용한 PMSM의 정밀 위치제어 (Precision Position Control of PMSM Using Neural Network Disturbance observer and Parameter compensator)

  • 고종선;진달복;이태훈
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제53권3호
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    • pp.188-195
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    • 2004
  • This paper presents neural load torque observer that is used to deadbeat load torque observer and gain compensation by parameter estimator As a result, the response of the PMSM(permanent magnet synchronous motor) follows that nominal plant. The load torque compensation method is composed of a neural deadbeat observer To reduce the noise effect, the post-filter implemented by MA(moving average) process, is adopted. The parameter compensator with RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller The parameter estimator is combined with a high performance neural load torque observer to resolve the problems. The neural network is trained in on-line phases and it is composed by a feed forward recall and error back-propagation training. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against the load torque and the Parameter variation. A stability and usefulness are verified by computer simulation and experiment.

외란관측기와 파라미터 보상기를 이용한 PMSM의 정밀위치 제어 (Precision Position Control of PMSM using Load Torque Observer and Parameter Compensator)

  • 고종선;이태훈
    • 전력전자학회논문지
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    • 제9권1호
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    • pp.42-49
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    • 2004
  • 본 논문은 데드비트 외란 관측기를 사용한 외부 부하 외란 보상과 파라미터 추정기에 의한 보상 이득의 조정을 나타내고 있다. 결론적으로 PMSM의 응답은 지표 시스템을 따른다. 부하 토크 보상 방법은 데드비트 관측기로 구성된다. 노이즈 영향을 감소시키기 위해 MA 처리에 의해 구현된 후단 필터를 적용하였고, RLSM 파라미터 추정기를 가진 파라미터 보상기가 주어진 실제 시스템의 이득 계산시 사용된 파라미터로 가상 동작하여 이득이 오차가 없는 것처럼 동작하게 한다. 제안된 추정기는 문제를 풀기 위해 고성능 외란 관측기와 조합하여 사용한다. 제안된 제어 시스템은 부하토크와 파라미터 변화에 대해 강인하고 정밀한 시스템이 된다. 이상의 제안된 시스템의 안정성과 유용함이 컴퓨터 시뮬레이션과 실험을 통하여 확인되었다.

Precision Position Control of PMSM using Neural Observer and Parameter Compensator

  • Ko, Jong-Sun;Seo, Young-Ger;Kim, Hyun-Sik
    • Journal of Power Electronics
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    • 제8권4호
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    • pp.354-362
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    • 2008
  • This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.

ATM망에서 사용자 변수 제어에 의한 감시 성능 개선에 관한 연구 (A study on improvement of policing perfomance by usage parameter control in asynchronous transfer mode networks)

  • 한길성;오창석
    • 한국통신학회논문지
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    • 제21권6호
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    • pp.1480-1489
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    • 1996
  • In ATM networks there are two methods in traffic control as schemes advancing the quality of service. One is reactive control after congestion and the other which is generally recommended, is preventive control before congestion, including connection admission control on call leel and usage parameter control, network parameter control, priority control and congestion control on cell level. In particular, usage parameter control is required for restricting the peak cell rate of bursy tracffic to the parameter negotiated at call set-up phase since the peak cell rate significantly influences the network quality of service. The scheme for progressing quality of service by usage parameter control is themethod using VSA(Virtual Scheduling Algorlithm) recommended ITU-T. The method using VSSA(Virtual Scheduling Suggested Algorlithm) in this paper is suggested by considering cell delay variation and token rate of leaky bucket, compared VSA and VSANT(Virtual Scheduling Algolithm with No Tolerance) with VSSA which polices violated cell probability of conformed peak cell rate and intentionally excessive peak cell rate. VSSA method using IPP(Interruped Poisson Process) model of input traffic source showed more quality of service than VSA and VSANT methods as usage parameter control because the suggested method reduced the violated cell probability of contformed peak cell rate and intentionally excessive peak cell rate.

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Bayesian parameter estimation을 적용한 RC 접합부 전단거동의 주요영향 요인 결정 (Determination of Key Influence Parameters on RC Joint Shear Behavior Using the Bayesian Parameter Estimation)

  • 김재홍;양종호;임덕기
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2011년도 정기 학술대회
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    • pp.328-331
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    • 2011
  • 준정적 횡하중을 재하 받는 철근콘크리트 보-기둥 접합부의 전단강도에 대한 주요 영향요인을 Bayesian parameter estimation의 신뢰성 이론 접목을 통해 검토하였다. 이와 같은 연구 scope의 수행을 위해 철근콘크리트 보-기둥의 실험 database가 구축되었다. 실험 database는 일정한 criteria을 적용하여 구축되었으며, 포함된 시편들은 최종적으로 접합부 내의 전단파괴가 지배하는 경우들이다. 포함된 시편들의 상세는 ACI (American Concrete Institute) 352R-02를 기준으로 평가되어졌다. 보-기둥 접합부의 전단강도에 영향 요인을 편중되지 않게 평가하고자, Bayesian parameter estimation의 신뢰성 이론을 적용하였다. Bayesian parameter estimation의 적용을 통해 전단강도에 영향이 적은 변수 (not informative parameter)를 순차적으로 제거 (stepwise removal process)함으로 주요 영향요인의 우선 순위를 확인할 수 있었다. 검토된 8개의 변수들 중에서, 횡하중을 재하 받는 철근콘크리트 보-기둥의 전단강도는 주로 콘크리트 압축강도, in-plane geometry, 종방향 보의 주철근 그리고 접합부 내의 구속철근 순으로 영향을 줌을 알 수 있었다.

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마이크로 스크류의 해석기반 판형 전조성형공정 연구 (Simulation based Process Design of Flat Die Thread Rolling for Micro Screw)

  • 박기동;송정한;이혜진;이근안;이낙규;이형욱;나승우
    • 한국소성가공학회:학술대회논문집
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    • 한국소성가공학회 2009년도 추계학술대회 논문집
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    • pp.62-65
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    • 2009
  • There have been strong demands for micro size screw with high precision due to miniaturization and integration trends for electronic products such as Hard Disk Drives. The thread rolling process for screw manufacturing are lower unit cost, reduced material utilization, and superior mechanical properties compared to the machining process. But little work has been done on the thread rolling of micro size screw. In this paper, we investigate thread rolling process using Finite Element Analysis (FEA) and parameter study for screw manufacturing. And we also carried out compression tests to obtain the material property and to implement into the FE tool for the numerical simulation. In case that parameter of relative position oldies is half length of pitch for maintaining the continuous thread profiles, we found that shear friction factor was 0.9 during the thread rolling process using FEA. We are trying to develop the thread rolling process using the FE-simulation to manufacture screws which have been commonly produced from the industrial level fabrication at present.

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고강도강 프런트 사이드멤버의 응력분포 최적화를 통한 스프링백 저감 (Stress-Based Springback Reduction of an AHSS Front Side Member)

  • 송정한;김세호;박성호;허훈
    • 소성∙가공
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    • 제15권4호
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    • pp.295-303
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    • 2006
  • Optimization is carried out to determine process parameters which reduce the amount of springback and improve shape accuracy of a deep drawn product in sheet metal forming process. The study uses the amount of stress deviation along the thickness direction in the deep drawn product as an indicator of springback instead of springback simulation. The scheme incorporates with an explicit elasto-plastic finite element method for calculation of the final shape and the stress deviation The optimization method adopts the response surface method in order to seek for the optimum condition of process parameters such as the blank holding force and the draw-bead force. The present scheme is applied to design of the variable blank holding force in an U-draw bending process and the application is further extend ε d to the design of draw-bead force in a front side member formed with advanced high strength steel (AHSS) sheets of DP60. Results show that design of process parameter is well performed to decrease the stress deviation through the thickness and to reduce the amount of springback. The present analysis provides a guideline in a design stage for controlling the springback based on the finite element simulation of the complicated parts.