• 제목/요약/키워드: Parameter Variation

검색결과 1,673건 처리시간 0.032초

온돌의 구들장과 땅바닥의 비정상 열전도 해석 (Transient Heat Conduction Through the Ondol Floor and Beat toss to the Ground)

  • 배순훈;김두천
    • 대한설비공학회지:설비저널
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    • 제4권1호
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    • pp.6-17
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    • 1975
  • For a periodic variation of the flue gas temperature the heat conduction through the Ondol floor was analysized. Also the heat loss to the ground was estimated. The floor thermal capacity, as a function of the floor thickness, has strong influence on the time lag of the temperature variation. It is an important design parameter for intermittent heating. Even for the steady periodic variation, there was significant heat loss to the ground below the Ondol floor.

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파라미터 해석을 통한 차량 성능 예측 기법 연구 (Study on the Prediction Technique of Vehicle Performance using Parameter Analysis)

  • 김기창;김찬묵;김진택
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2009년도 추계학술대회 논문집
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    • pp.647-653
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    • 2009
  • Taguchi parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used SN (Signal to Noise) ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. This paper describes the prediction technique of vehicle performance using parameter analysis to reduce man hour and test development period as well as to achieve stable NVH performance. Design engineer could efficiently decide the design variable using parameter analysis database in early design stage. These improvements can reduce the time needed to develop better vehicles.

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차량 파라미터 변화에 강건한 적응형 신경회로망 기반 경로추종제어기 (Design of Adaptive Neural Networks Based Path Following Controller Under Vehicle Parameter Variations)

  • 신동호
    • 드라이브 ㆍ 컨트롤
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    • 제17권1호
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    • pp.13-20
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    • 2020
  • Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

IPMSM 드라이브의 온라인 파라미터 추정을 위한 신경회로망 (Neural Network for on-line Parameter Estimation of IPMSM Drive)

  • 이홍균;이정철;정동화
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제53권5호
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    • pp.332-337
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    • 2004
  • A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying. parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

파라미터 변화에 무관한 인버터 구동 PMSM의 데드타임 보상 기법 (Dead Time Compensation Scheme Independent of Parameter Variations in an Inverter-fed PMSM Drive)

  • 김경화
    • 조명전기설비학회논문지
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    • 제25권4호
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    • pp.124-134
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    • 2011
  • A new dead time compensation scheme that can exactly estimate the dead time and inverter nonlinearity under parameter variations is proposed for a PWM inverter-fed PMSM drive. The proposed scheme uses the fact that the sixth harmonic component in total disturbance estimated under the presence of various uncertainties is mainly caused by the dead time and inverter nonlinearity. The total disturbance due to the parameter variations as well as the dead time and inverter nonlinearity is estimated by the adaptive scheme. The sixth harmonic component is extracted from this total disturbance through harmonic analysis. The obtained sixth harmonic is processed by the PI controller to estimate the disturbance caused by the dead time and inverter nonlinearity in the stationary reference frame. The effectiveness of the proposed scheme is verified. Without requiring an additional hardware, the proposed scheme can effectively compensate the dead time and inverter nonlinearity even under the parameter variations.

유도전동기 자속추정기의 특성해석 (Analysis of Induction Machine Flux Observer)

  • 남현택;이경주;최종우;김흥근
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2001년도 추계학술대회 논문집
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    • pp.7-10
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    • 2001
  • To obtain a high performance in a direct vector controlled induction machine, it is essential to correct estimation of rotor flux. The accuracy of flux observers for induction machines inherently depends on parameter sensitivity. This paper presents an analysis method for conventional flux observers using Parameter Sensitivity. The Parameter sensitivity is defined as the ratio of the percentage change in the system transfer function to the percentage change of the parameter variation. We define the ratio between real flux and estimated flux as the transfer function, and analyzed a parameter sensitivity of this transfer function.

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신경회로망을 이용한 IPMSM 드라이브의 온라인 파라미터 추정 (On-line Parameter Estimation of IPMSM Drive using Neural Network)

  • 최정식;고재섭;정동화
    • 제어로봇시스템학회논문지
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    • 제13권5호
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    • pp.429-433
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    • 2007
  • A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

신경회로망을 이용한 IPMSM 드라이브의 온라인 파라미터 추정 (On-line Parameter Estimation of IPMSM Drive using Neural Network)

  • 최정식;고재섭;이정호;김종관;박기태;박병상;정동화
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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    • pp.207-209
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    • 2006
  • A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

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

  • 고종선;이용재
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2002년도 전력전자학술대회 논문집
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    • pp.285-288
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    • 2002
  • This paper presents external load disturbance compensation 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 deadbeat observer To reduce of the noise effect, the post-filter, which is implemented by MA process, is adopted. 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 load 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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