• 한국정보전자통신기술학회논문지
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• 제5권3호
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• pp.117-126
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• 2012

논문에서는 극저속 영역 및 저속 영역에서 안정적이고 동특성이 우수한 벡터제어 시스템을 구성하여, 축소차원 상태관측기를 이용한 순시속도 관측기와 극저속 제어에 관한 방법을 제안하였다. 본 시스템에서 제안된 관측기는 축소차원 상태관측기를 부하토크 추정에 적용하여 속도추정에 이용함으로서 시스템구성을 간단히 구현하면서도 극저속 영역에서 정확한 순시속도 추정이 가능하였다. 또한, 시스템 잡음에 의한 영향을 줄이고, 관측기의 극을 변화시키는 일 없이 부하외란이나 모델화 오차, 측정 잡음 등에 강인한 유도전동기 속도제어 시스템을 제시하였다.

• 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 2004년도 하계학술대회 논문집 D
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• pp.2304-2306
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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.

• International Journal of Automotive Technology
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• 제6권5호
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• pp.475-481
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• 2005

This paper deals with the algorithm of estimating the longitudinal speed of a braking vehicle using measurements from an accelerometer and a standard wheel speed sensor. We evolve speed estimation algorithms of increasing complexity and accuracy on the basis of experimental tests. A final speed estimation algorithm based on a Kalman filtering is developed to reduce measurement noise of the wheel speed sensor, error of the tire radius, and accelerometer bias. This developed algorithm can give peak errors of less than 3 percent even when the accelerometer signal is significantly biased.

• 한국자동차공학회논문집
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• 제10권6호
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• pp.234-240
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• 2002

This paper treats the problem of estimating the longitudinal velocity of a braking vehicle using measurements from an accelerometer and wheel speed data from standard anti-lock braking wheel speed sensors. We develop and experimentally test three velocity estimation algorithms of increasing complexity. The algorithm that works the best gives peak errors of less than 3 percent even when the accelerometer signal is significantly biased.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 A
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• pp.9-11
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• 1998

Most of sensorless algorithms are based on motor equations including electrical and mechanical parameters. However, parameter variation and uncertain error decrease the accuracy of speed estimation of PMSM. This paper investigates the sensorless speed control of PMSM considering parameter variation. The proposed algorithm use the speed compensator which is robust in parameter variation and error. The simulation and experimental results indicate good performances.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 추계학술대회 논문집
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• pp.3-6
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• 2002

In a conventional speed sensorless stator flux-oriented(SFO) induction motor drive system, when the estimated speed is transformed into the sample-data model using the first-forward difference approximation, the sampled data model has a modeling error which, in turn, produces an error in the rotor speed estimation. The error included in the estimated speed is removed by the use of a low pass filter (LPF). As the result, the delay of the estimated speed occurs in transients by the use of the LPF This paper investigates the problem of a conventional speed sensorless SFO system due to the delay of estimated speed in the filed weakening region. In addition, this paper proposes a method to estimate exactly speed by using Luenberger observer, The proposed method is verified by experiment with a 5-hp induction motor drive.

• Journal of Power Electronics
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• 제16권6호
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• pp.2150-2161
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• 2016

Mechanical and electrical parameter uncertainties cause dynamic and static estimation errors of the rotor speed and position, resulting in performance deterioration of sensorless control systems. This paper applies an extended nonlinear observer to interior permanent magnet synchronous motors (IPMSM) for the simultaneous estimation of the rotor speed and position. Two compensation methods are proposed to improve the observer performance against parameter uncertainties: an on-line rotational inertia adjustment approach that employs the gradient descent algorithm to suppress dynamic estimation errors, and an equivalent flux error compensation approach to eliminate static estimation errors caused by inaccurate electrical parameters. The effectiveness of the proposed control strategy is demonstrated by experimental tests.

• International Journal of Control, Automation, and Systems
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• 제3권1호
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• pp.79-86
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• 2005

In this paper, an estimator scheme for the rotor speed and flux of an induction motor is proposed on the basis of a fourth-order electrical model. It is assumed that only the stator currents and voltages are measurable, and that the stator currents are bounded. There are a number of common terms in the motor dynamics, and this is utilized to find a simple error model involving some auxiliary variables. Using this error model, the state estimation problem is converted into a parameter estimation problem assuming that the rotor speed is constant. Some stability properties are given on the basis of Lyapunov analysis. In addition, the rotor resistance, which varies with the motor temperature, can also be estimated within the same framework. The effectiveness of the proposed scheme is demonstrated through computer simulations and experiments.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권10호
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• pp.690-696
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• 2004

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(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.