• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.1005-1013
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• 2012

In this paper, the induction motor in indirect vector control method modeling, from indirect vector control method it undergoes an influence to the $1/{\tau}$. When changing a rotor resistance because being like this quality Matlab/Simulink where it will make what kind of effect in speed presumption it led proposed control system used microprosser TMS320C31 DSP for high speed processing. The effectiveness of the proposed system is verified by simulation and experimental results. This result shows highly characteristic speed estimation and robust character of load regulation. and the flux which it follows in change of parameter and speed presumption it was under simulation and get the good result which it comes to get it analyzed.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.50-52
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• 2006

This paper Proposes a new method of on-line estimation for rotor resistance of the induction motor in the indirect vector controlled drive, using artificial neural network (ANN). The back propagation algorithm is used for training of the neural networks. The error between the desired state variable of an induction motor and actual state variable of a neural network model is back propagated to adjust the weight of a neural network model, so that the actual state variable tracks the desired value. The performance of rotor resistance estimator and torque and flux responses of drive, together with these estimators, are investigated variations rotor resistance from their nominal values. The rotor resistance are estimated analytically, using the proposed ANN in a vector controlled induction motor drive.

• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.27-34
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• 2006

This paper proposes a new method of on-line estimation for rotor resistance of the induction motor in the indirect vector controlled drive, using artificial neural network (ANN). The back propagation algorithm is used for training of the neural networks. The error between the desired state variable of an induction motor and actual state variable of a neural network model is back propagated to adjust the weight of a neural network model, so that the actual state variable tracks the desired value. The performance of rotor resistance estimator and torque and flux responses of drive, together with these estimators, are investigated variations rotor resistance from their nominal values. The rotor resistance are estimated analytically, using the proposed ANN in a vector controlled induction motor drive.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.285-288
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• 1996

Iron loss is a possible source of performance deterioration, especially for a torque regulation, in field oriented induction machine. In this paper, study on the model of an induction machine with iron losses, a flux estimation strategy, the design of direct and indirect field oriented controller, a precise torque regulation scheme and the determination of a core lost resistance are discussed. Simulation and experimental results are also included and show the effectiveness of the proposed analysis and the proposed control strategy.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.201-205
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• 2004

A method for driving and position sensing of TSRM(Toroidal Switched Reluctance Motor) using the search coil is presented in this paper. Position information of the rotor is essential for SRM drives. The rotor position sensor such as an opto-interrupter or high performance encoder is generally used for the estimation of rotor position. However, these discrete position sensors not only add complexity and cost to the system but also tend to reduce the reliability of the drive system. In order to solve these problems, in the proposed method, rotor position detection is achieved using the voltage waveforms induced by the time varying flux linkage in the search coils, and then the appropriate phases are excited to drive the SRM. But the search coil EMF is generated only when the motor rotates. Therefore the rotor position sensing method at standstill is also suggested.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.162.5-162
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• 2001

This paper presents a indirect vector control system for induction motors using an adaptive fuzzy logic(AFL) speed estimator. The proposed speed estimator is based on the MRAS(Mode Referece Adaptive System) scheme. In general, the MRAS speed estimation approaches are more simple than any other strategies. However, there are some difficulties in the scheme, which are strong sensitivity to the motor parameters variations and necessity to detune the estimator gains caused by different speed area. In this paper, the AFL speed estimator is proposed to solve the problems. The structure of the proposed AFL is very simple. The input of the AFL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed. Moreover, the back propagation algorithm is combined to adjust the parameters of the fuzzy logic to the most appropriate values during the operating the system. Finally, the validity of the ...

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2161-2163
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• 2003

This Paper presents a vector control method for the parallel-connected motor drive system. The new estimation scheme of rotor flux position is presented to reduce sensitivity due to load difference between the motors. To confirm the validity of the proposed control method, we compare a simulation result of the proposed control method with that of the conventional indirect vector control method. The simulation results show that the proposed control method is more effective step change in load torque.

• Journal of Power Electronics
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• v.5 no.3
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• pp.173-179
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• 2005

In this paper, a very low cost and robust sensing method for the rotor position of a TSRM(Toroidal Switched Reluctance Motors) is described. Position information of the rotor is essential for SRM drives. The rotor position sensor such as an opto-interrupter or high performance encoder is generally used for the estimation of rotor position. However, these discrete position sensors not only add complexity and cost to the system but also tend to reduce the reliability of the drive system. In order to solve these problems, in the proposed method, rotor position detection is achieved using voltage waveforms induced by the time varying flux linkage in the search coils, and then the appropriate phases are excited to drive the SRM. But the search coil's EMF is generated only when the motor rotates. Therefore the rotor position sensing method using squared Euclidean distance at a standstill is also examined. The simulation and experimental results are presented to verify the performance of the proposed method in this paper.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.301-311
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• 2017

Aerosol optical properties as well as vertical location of layer can alter the radiative balance of the Earth by reflecting and absorbing solar radiation. In this study, radiative transfer model (RTM) and satellite-based analysis have been used to quantify the top-of-atmosphere (TOA) radiative effect of aerosol layers in the cloudy atmosphere of the northeast Asia. RTM simulation results show that the atmospheric warming effect of aerosols increases with their height in the presence of underlying cloud layer. This relationship is higher for stronger absorbing aerosols and higher surface albedo condition. Over study region ($20-50^{\circ}N$, $110-140^{\circ}E$) and aerosol event cases, it is possible to qualitatively identify absorbing aerosol effects in the presence of clouds by combining the UV Absorbing Aerosol Index (AAI) derived from Total Ozone Mapping Spectrometer (TOMS), cloud parameters derived from the Moderate Resolution Imaging Spectro-radiometer (MODIS), with TOA Upward Shortwave Flux (USF) from the Clouds and the Earth's Radiant Energy System (CERES). As the regional-mean radiative effect of aerosols, 6 - 26 % lower the USF between aerosols and cloud cover is taken into account. These results demonstrate the importance of estimation for the accurate quantification of aerosol's direct and indirect effect.