• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1407-1410
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• 1997

Advanced sensor design and filtering technology have been studied to obtain information for condition monitoring and diagnostics inmachining processes. To develope and economic monitoring system in end milling processes, indirect and reliable type of cutting force estimators were required. In this paper, an estimation method of cutting forces during end milling processes was studied through the measurement of current signals obtained from spindle and feeddrive motors. Cutting force and torque models were derived from the cutting geometry in down milling processes. Relationships between motor currents and cutting forces were also developed in the form of AC and DC components from the developed force models. The validity of the cutting force estimator was confirmed by the experiments under various cutting conditions.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.207-215
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• 2017

In this paper we study pooling effects in Bayesian testing procedures of independence for contingency tables from small areas. In small area estimation setup, we typically use a hierarchical Bayesian model for borrowing strength across small areas. This techniques of borrowing strength in small area estimation is used to construct a Bayes test of independence for contingency tables from small areas. In specific, we consider the methods of direct or indirect pooling in multinomial models through Dirichlet priors. We use the Bayes factor (or equivalently the ratio of the marginal likelihoods) to construct the Bayes test, and the marginal density is obtained by integrating the joint density function over all parameters. The Bayes test is computed by performing a Monte Carlo integration based on the method proposed by Nandram and Kim (2002).

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.363-366
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• 1990

In the indirect vector control method, the rotor resistance variation caused by operating temperature change is an undesirable nature. A new adaptation algorithm to compensate for the rotor resistance change based on the on-line estimation of field vector which requires the measurements of stator voltage and rotor speed is presented in this paper. Also minimum variance controller is presented for the adaptive control performance. This algorithm has been tested by simulating the induction machine using a digital computer and the results are discussed.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.50 no.1
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• pp.30-36
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• 2001

This paper introduces a new indirect rotor position estimation algorithm for the SRM sensorless control, based on the magnetizing curves of aligned and unaligned rotor positions. Through the basic test method, the complete SRM magnetizing characterization is first constructed using a neural network training, and then used to estimate the rotor position. And also, the optimal phase is selected by the phase selector. In order to verify this approach, the proposed rotor position estimation algorithm using a neural network learning data is investigated. The experimental results show that the proposed control algorithm can be effectively applied to SRM sensorless control.

• Journal of the Korean Society for Railway
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• v.14 no.3
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• pp.211-215
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• 2011

Generally, sound power is one of the most significant factors to predict and assess noise from sound sources. However, many researchers developed indirect methods to calculate the sound power with noise level because it is impossible to measure sound power directly while a train is running. In this paper, we propose a method to estimate sound power generated due to wheel/rail interaction and propulsive equipment from the measurement of noise emitted from rolling stocks and verify the estimation method by comparing with the other sound power estimation formula. We also analyze the sound power of rolling stocks which are operating in domestic lines such as EMU, Mukoonghwa, KTX using the method proposed in this paper.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1167-1175
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• 2022

In this study, management index method has been developed to estimate the level of deterioration, applied to Cheongju city, and compared with the previous estimation methods of deterioration level of water distribution system. From the results, distribution systems of Yullyang, Naedeok1 and Yongam2 are found to be seriously deteriorated. And it was also found that probability of pipe breakage was estimated as 3.21%, 4.64% which is highest level at the steel pipe of 200 mm and 300 mm diameter. It was found that risk degree was estimated as 0.2609, 0.2644 by using management index method in Naedeok1 which is the most dangerous distribution system in the city. It was also found that results of risk analysis by management index method have been similar with the results of safety analysis by reliability method and indirect estimation method of deterioration level. Therefore, newly developed management index method can be applied and may be useful to the estimation of deterioration level for the future maintenance and management of water distribution system.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.