• Title/Summary/Keyword: Real-time parameter estimation

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A Study on the Parameter Estimation of an Induction Motor using Neural Networks (신경회로망을 이용한 유도전동기의 피라미터 추정)

  • 류한민;김성환;박태식;유지윤
    • Proceedings of the KIPE Conference
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    • 1998.07a
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    • pp.225-229
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    • 1998
  • If there is a mismatch between the controller programmed rotor time constant and the actual time constant of motor, the decoupling between the flux and torque is lost in an indirect rotor field oriented control. This paper presents a new estimation scheme for rotor time constant using artificial neural networks. The parameters of induction motor model organize 2 layer neural to be weight between neuron, which is proposed new in this paper. This method makes networks simple, so its brings not only the improvement in speed but simplification in calculation. Furthermore, it is possible to estimated rotor time constant real time through on-line learning without using off-line learning. The digital simulation and the experimental results to verify the effectiveness of the new method are described in this paper.

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A Neural Multiple LMS Based ANC System for Reducing Acoustic Noise of High-Speed Trains (신경회로망 다중 LMS 기법을 이용한 고속철도의 실내소음저감을 위한 ANC 시스템)

  • Cho, Hyun-Cheol;Lee, Kwon-Soon;Nam, Hyun-Do
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.58 no.4
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    • pp.385-390
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    • 2009
  • This paper presents a novel active noise control (ANC) system using least mean square (LMS) algorithm and neural network approach for decreasing acoustic noise signals inside high-speed trains. We construct a LMS framework as a nominal ANC system and additionally design an artificial single-layered perceptron model as an auxiliary ANC which is aimed to reduce real-time residuary noise due to its nonstationary and uncertain nature. Parameter vector of the hybrid ANC is determined through online estimation to realize an adaptive ANC configuration by means of the steepest descent algorithm. We achieve simulation experiment to demonstrate the proposed ANC system employing realistic acoustic noise signals measured in Korea Train eXpress (KTX).

A Stabilization Method for Rotated and Translated Images (회전 및 병진 흔들림 영상의 안정화 기법)

  • Seok Ho-Dong;Lyou Joon
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.8
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    • pp.810-817
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    • 2006
  • This paper presents a rotational motion estimation and correction technique for digital image stabilization. An equivalent rotation model is derived so as to accommodate a combined rotational and the translational motion. Thanks to this simplification, the suggested estimation algorithm can directly find the rotational center using geometric characteristic of local motion vectors instead of using searching method. And we also present recursive version of frame to reference algorithm(FRA) for the real time implementation. The proposed DIS system does not require time consuming parameter searching process, while showing comparatively good performance compared with the previous ones. To show the effectiveness of the DIS scheme, the algorithm has been implemented on the DSP based hardware system and experimental results are also discussed.

Forecasting the Flood Inflow into Irrigation Reservoir (관개저수지의 홍수유입량 예측)

  • 문종필;엄민용;박철동;김태얼
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 1999.10c
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    • pp.512-518
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    • 1999
  • Recently rainfall and water evel are monitored via on -line system in real-time bases. We applied the on-line system to get the rainfall and waterlevel data for the development of the real-time flood forecasting model based on SCS method in hourly bases. Main parameters for the model calibration are concentration time of flood and soil moisture condition in the watershed. Other parameters of the model are based on SCS TR-%% and DAWAST model. Simplex method is used for promoting the accuracy of parameter estimation. The basic concept of the model is minimizing the error range between forcasted flood inflow and actual flood inflow, and accurately forecasting the flood discharge some hours in advance depending on the concentration time. The flood forecasting model developed was applied to the Yedang and Topjung reservoir.

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A STUDY OF PROCESS PARAMETER MONITORING AND INTELLIGENT QUALITY ESTIMATION DURING RESISTANCE SPOT WELDING

  • Kim, Taehyung;Yongjun Cho;Kim, Yongjae;Sehun Rhee
    • Proceedings of the KWS Conference
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    • 2002.10a
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    • pp.330-335
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    • 2002
  • Resistance spot welding is one of the most widely used processes in sheet metal fabrication. Quality assurance of welding has been important to increase the productivity. In this study, weld quality estimation using primary circuit dynamic resistance applied to the in-process real-time systems. For quality estimation, factors relating to quality were extracted from the dynamic resistance, measured in the timer. The relationship between these factors and weld quality was determined through a artificial neural network model. This method has the advantage over the conventional one, such as obtaining the quality information without the use of extra devices.

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Low Noise Time-Frequency Analysis Algorithm for Real-Time Spectral Estimation (실시간 뇌파 특성 분석을 위한 저잡음 스펙트럼 추정 알고리즘)

  • Kim, Yeon-Su;Park, Beom-Su;Kim, Seong-Eun
    • Journal of IKEEE
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    • v.23 no.3
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    • pp.805-810
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    • 2019
  • We present a time-frequency analysis algorithm based on the multitaper method and the state-space frameworks. In general, time-frequency representations have a trade-off between the time duration and the spectral bandwidth by the uncertainty principle. To optimize the trade-off problems, the short-time Fourier transform and wavelet based algorithms have been developed. Alternatively, the authors proposed the state-space frameworks based on the multitaper method in the previous work. In this paper, we develop a real-time algorithm to estimate variances and spectrum using the state-space framework. We test our algorithm in spectral analysis of simulated data.

Real-Time Vehicle Detector with Dynamic Segmentation and Rule-based Tracking Reasoning for Complex Traffic Conditions

  • Wu, Bing-Fei;Juang, Jhy-Hong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.12
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    • pp.2355-2373
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    • 2011
  • Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.

A Pole-Assignment ACC System in the Peripheral End Milling Process (엔드밀링 공정에서 극점배치 구속적응제어 시스템)

  • Chung, Sung-Chong
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.5 no.2
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    • pp.63-72
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    • 1996
  • In order to regulate the cutting force at a desired level during peripheral end milling processes a feedrate override Adaptive Control Constraint (ACC) system was developed. The feedrate override function was accomplished through a development of programmable machine controller (PMC) interface technique on the NC controller, Nonlinear model of the cutting process was linearized as an adaptive model with a time varying process parameter. An integral type estimator was introduced for on-line estimation of the cutting process parameter, Zero order hold digital control methodology which uses pole-assignment concept for tuning of PI controllers was applied for the ACC system. Performance of the ACC system wsa confirmed on the vertical machining center equipped with fanuc OMC through a large amount of experiment.

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Maximum Efficiency Control of an Induction Motor Drive by Parameter Adaptive Compensation (파라미터 적응보상에 의한 유도전동기의 최대효율 제어기법)

  • Shon, Jin-Geun;Choi, Myung-Gyu;Park, Jong-Chan;Na, Chae-Dong;Lee, Sung-Bum
    • Proceedings of the KIEE Conference
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    • 2000.07e
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    • pp.162-166
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    • 2000
  • In this paper, a maximum efficiency control technique of real-time processing in which parameter variation is compensated in vector control of an induction motors(I.M.) is proposed. Based on equivalent model of I.M., a loss minimization factor(LMF) with the variations of speed is derived. To solve problem of inaccuracy of LMF curves due to machine parameter variation, rotor resistance estimation is performed by using instantaneous reactive power. The estimated rotor resistance values are applied to the maximum efficiency control with a LMF.

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Quasi-Optimal DOA Estimation Scheme for Gimbaled Ultrasonic Moving Source Tracker (김발형 초음파 이동음원 추적센서 개발을 위한 의사최적 도래각 추정기법)

  • Han, Seul-Ki;Lee, Hye-Kyung;Ra, Won-Sang;Park, Jin-Bae;Lim, Jae-Il
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.2
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    • pp.276-283
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    • 2012
  • In this paper, a practical quasi-optimal DOA(direction of arrival) estimator is proposed in order to develop a one-axis gimbaled ultrasonic source tracker for mobile robot applications. With help of the gimbal structure, the ultrasonic moving source tracking problem can be simply reduced to the DOA estimation. The DOA estimation is known as one of the representative long-pending nonlinear filtering problems, but the conventional nonlinear filters might be restrictive in many actual situations because it cannot guarantee the reliable performance due to the use of nonlinear signal model. This motivates us to reformulate the DOA estimation problem in the linear robust state estimation setting. Based on the assumption that the received ultrasonic signals are noisy sinusoids satisfying linear prediction property, a linear uncertain measurement model is newly derived. To avoid the DOA estimation performance degradation caused by the stochastic parameter uncertainty contained in the linear measurement model, the recently developed NCRKF (non-conservative robust Kalman filter) scheme [1] is utilized. The proposed linear DOA estimator provides excellent DOA estimation performance and it is suitable for real-time implementation for its linear recursive filter structure. The effectiveness of the suggested DOA estimation scheme is demonstrated through simulations and experiments.