• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.140-143
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• 1991

This paper describes a compensation method for the rotor resistance variation of induction machines in speed sensor-less vector control system using MRAS(model reference adaptive system). In case of rotor resistance variation, the analysis of the conventional speed sensor-less vector control system using MRAS is presented and the compensation method for rotor resistance variation using Fuzzy logic is proposed. In order to confirm the performance of the proposed algorithm, computer simulation is performed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.148-151
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• 1991

This paper describes the vector control system estimates rotor speed based on MRAS(Model Reference Adaptive Control) and this estimate is used for speed feedback control. The stability of speed estimator is proved on the basis of hyperstability theory. In order to improve the performance of speed control, the load torque is estimated by load torque observer and speed controller compensates this estimate value. Thus the robust vector control system against load torque disturbance is constructed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.660-662
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• 2004

This paper proposes an Intelligent Speed Estimator in order to realize the speed-sensorless vector control of an induction motor. Intelligent Speed Estimator used Model Reference Adaptive System which has Fuzzy-Neural adaptive mechanism as Speed Estimation method. The Intelligent Speed Estimator estimates the speed of an induction motor with a rotor flux of a reference model and adjustable model in MRAS. The Intelligent Speed Estimator reduces the error of the rotor flux between the voltage flux model and the current flux model using the error and the change of error as input of the Estimator. The computer simulation is executed to verify the propriety and the effectiveness of the proposed speed estimator.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 학술대회 논문집 전문대학교육위원
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• pp.160-164
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• 2007

MRAS observer, which is based on adaptive control theory, estimates speed and position by using optimal observer gains on the basis of Lyapunov stability theory. However, in case of MRAS theory, position estimation error is in existence because of non-linearity for inductance variation and limit cycles for position estimation. The adaptive sliding observer based on the variable structure control theory estimates the speed and position for zero of estimation error by using the sliding surface equal to the error between speed and position estimation. The binary observer estimates the rotor speed and rotor flux with alleviation of the high-frequency chattering, and retains the benefits achieved in the conventional sliding observer, such as robustness to parameter and disturbance variations. The speed and position sensorless control of SRM under the load and inductance variation is verified by the experimental results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 B
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• pp.1135-1137
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• 2001

본 연구는 자계방향 기준 벡터제어 이론에 기초하여 속도 센스리스 벡터제어를 구현한다. 벡터제어는 상태량에 기초한 MRAS (MRAS: Model Reference Adaptive System)방법은 이득정수의 결정이 어려운 결점을 가지고 있다. 여기서는 관측기 이론에 기초하여 2차자속 관측기와 전류센스에서 검출한 전류값으로 속도추정을 행하는 새로운 속도 추정법을 제안한다. 그리고 제안한 방법이 자계 방향 벡터제어 시스템의 실현에 가능성이 있음을 시뮬레이션으로 검토한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 B
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• pp.1212-1214
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• 2001

In this paper ASIC design technique using VHDL is applied to MRAS based speed sensorless control of induction motor. ASIC for MRAS based speed sensorless control is designed through the description of speed estimator using FSM, stator voltage controller, flux angle detector, coordinate transformation, and inverter switching signal output. Finally the above system has been implemented on the FPGA (VERTEX XCV400HQ240). Simulation and experiment have been performed to verify the performance of the designed ASIC.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1999년도 전력전자학술대회 논문집
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• pp.540-543
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• 1999

This paper describes a speed sensorless algorithm for vector control system with compensated stator resistance and rotor time constant of induction motor using a model reference adaptive system(MRAS). The system are composed of two MRAC, one is a rotor speed estimation and a stator resistor identification by back-EMF observer, other is used to identify rotor time constant by magnetizing current observer, so that the estimation can be cover a very low speed range with a robust control. The suggest control strategy and estimation method have been validated by simulation study. In the simulation using Matlab/Simulik, the proposed speed sensorless vector control system are shown to operate very well in spite of variable rotor time constant and load fluctuation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.139.4-139
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• 2001

The thesis propose the sensorless vector control method that estimates the rotor speed using stator current. The estimated speed is used as feedback in a vector control system. The conventional MRAS structure has a problem the error output is decreasing as estimated speed error is increasing and the estimation performance is not robust when mutual inductance has been changed. In the proposed method, error output is proportional to estimated speed error. The described technique is less complex, robust to variations of mutual inductance. This new method can achieve much wider bandwidth speed control than that of the conventional MRAS structure.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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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 ...

• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 Proceedings ICPE 98 1998 International Conference on Power Electronics
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• pp.768-773
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• 1998

The speed control of SRM(Switched Reluctance Motor) needs the accurate position and speed data of rotor. This information is generally provided by a shaft encoder or resolver. In some cases, the environment is which the motor operates may cause difficulties in maintaining the satisfactory position detection performance. Therefore, the elimination of the position and speed sensor has gained wide attention. In this paper, a new algorithm for estimation of rotor position and speed is described for the SRM drives. This method uses is nonlinear adaptive observer using the MRAS(Model Reference Adaptive System). The observer is proved by Lyapunov Stability Theory. This algorithm was implemented with a TMS320C31 DSP. Experiment results prove that the observer is able to estimate the speed and position with a little errors.