• The Transactions of the Korean Institute of Power Electronics
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• v.1 no.1
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• pp.12-19
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• 1996

The purpose of this paper is the improvement of the speed control characteristics of induction machines suited the low resolution incremental-type encoder in a low speed region. In order to improve the control characteristics in a low speed range, we propose that the instantaneous speed control method by the instantaneous speed detection which is implemented by the disturbance torque observer. Also, in case of the speed control by the instantaneous speed detection, the simple estimation method of the mechanical inertia moment is proposed. We will the carry out the mathematical verification of the proposed theory by the theoretic advisement connected with the convergence relationship of the estimated inertia moment to the real mechanical inertia moment. Computer simulations and experiments by the IGBT inverter adopting DSP is performed to verify the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.737-740
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• 2009

In this paper, in order to improve the location estimation error existing in RTLS(Real Time Location Service) system for the mobility individual, we proposed a method of speed-adaptive location estimation that the transmitting signaling period is adaptively changed according to the changing speed of a mobility individual for each location interval. To get the more accurate location estimation values, we analyzed both the location values measured by Hybrid(TDOA and RSSI) method by using AeroScout TM RTLS system and the estimated value obtained from the theoretical calculation by using the Least Squares Method. Finally, we compared the analyzed values with a real location of mobility individual. From the experimental results based on our proposed method, it can be seen that the location estimation error for the real location of a mobility individual can be improved.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.3
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• pp.125-132
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• 2002

PMSMS (permanent magnet synchronous motors) are widely used in industrial applications and home appliances because of their high torque to inertia ratio, superior power density, and high efficiency. For high performance control, accurate informations about the rotor position is essential. Sensorless algorithms have lately been studied extensively due to the high cost of position sensors and their low reliability in harsh environments. A novel position sensorless speed control for PMSMs uses indirect flux estimation and is presented in this paper. Rotor position and angular velocity are estimated by the proposed indirect flux estimation. Linkage flux and magnetic field flux are calculated by the voltage equations and the measured phase current without any integration. Instead of linkage flux calculation with integral operation, indirect flux and differential magnetic field are used for the estimation of rotor position. A proper rejection technique fur current noise effect in the calculation of differential linkage flux is introduced. The proposed indirect flux detecting method is free from the integral rounding error and linkage flux drift problem, because differential linkage flux can be calculated without any integral operation. Furthermore, electrical parameters of the PMSM can be measured by the proposed TCM (time compression method) for soft starting and precise estimation of rotor position. The position estimator uses accurate electrical parameters that are obtained from the proposed TCM at starting strategy. In the operating region, a proper compensation method fur temperature effect can compensate fir the estimation error from the variation of electrical parameters. The proposed novel position sensorless speed control scheme is verified by the experimental results.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.545-550
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed estimation and control of speed of induction motor using ANN Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.35-41
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• 2014

This paper presents a design method of programmable low pass filter(PLPF) which reduce an estimation error of a zero crossing point(ZCP) for a high speed brushless DC(BLDC) motor drive. BLDC motor sensorless drive is possible by estimation of ZCP. The ZCP estimated by detecting a change of back-EMF polarity has the estimation error because noises exist on the measured back-EMF. Therefore a calculated commutation timing using the ZCP is inaccurate. And the inexact commutation timing leads to ripples of 3-phase current and degradation of drive performance. This paper proposes the design method of the PLPF to overcome these problems. First, a speed calculated a inaccurate period of the ZCP is analyzed in the frequency domain. Then, the PLPF that has varying cut-off frequency according to change of the speed is designed on the frequency analysis result. The proposed method is verified by the experiment.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.806-811
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• 1994

Two kinds of static and dynamic state estimation methods are newly discussed for the problem of the measurement disturbance of environmental low-frequency noise in the presence of wind-induced noise. First, the probability characteristics of wind-induced noise are discussed in the form of probability distribution conditioned by wind speed, based on the simultaneous observation of the wind-induced noise and wind speed near a microphone. Next, especially form the viewpoint of simplicity for practical use, two kinds of static and dynamic state estimation methods are discussed. The static estimation method using the information on wind speed is fundamentally supported by the conservation principle of energy sum. The dynamic one is the method by using a recursive digital filter with the parameters successively renewed by the information on wind speed. This can be also simplified by using well-know Kalman filter under the assumption of the Gaussian distribution. The effectiveness of proposed two estimation methods are shown through experiments under a breezy condition in the open filed.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.565-571
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• 2005

We present a novel speed estimation of a Permanent Magnet Synchronous Motor(PMSM) based on Support Vector Regression(SVR). The proposed method can estimate wide speed range, including 0.33Hz with full load, accurately in the steady and transient states where motor parameters variations are known without parameter estimator. Moreover, the method does not need offline training previously but is trained on-line. The training starts with the PMSM operation simultaneously and estimates the speed in real time. The experimental results shows the validity and the usefulness of the proposed algorithm for the 0.4Kw PMSM DSP(TMS320VC33) drive system.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.287-297
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• 2018

To improve the performance of sensorless induction motor (IM) drives, a novel speed estimation method based on the real-time adaptive extended Kalman filter (RAEKF) is proposed in this paper. In this algorithm, the fuzzy factor is introduced to tune the measurement covariance matrix online by the degree of mismatch between the actual innovation and the theoretical. Simultaneously, the fuzzy factor can be continuously self-tuned tuned by the fuzzy logic reasoning system based on Takagi-Sugeno (T-S) model. Therefore, the proposed method improves the model adaptability to the actual systems and the environmental variations, and reduces the speed estimation error. Furthermore, a simple exponential function based on the fuzzy theory is used to reduce the computational burden, and the real-time performance of the system is improved. The correctness and the effectiveness of the proposed method are verified by the simulation and experimental results.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.47-48
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• 2005

This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.983-984
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• 2011

An effective estimation method of equivalent circuit parameters of three-phase induction motor by using FEM is presented in this paper. Arbitrary three torque-speed points at asynchronous speed on the torque-speed curve are required by using time-stepping FEM, then the equivalent circuit parameters of IM can be calculated rapidly with presented method. After obtaining the equivalent circuit parameters, the general analysis method based on equivalent circuit can be used to get entire torque-speed curve very quickly. Although the purely numerical method such as FEM also can estimate torque-speed curve directly and accurately, however, usually this process is time consuming.