• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.369-373
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• 2001

Multilevel inverter has attracted great interest in high-voltage high-power field because of its less distorted output. In this paper, a direct torque control (DTC) technique based on a three-level neutral-point-clamped (NPC) inverter is presented. In order to solve the intrinsic neutral-point voltage-balancing problem and to obtain a high performance DTC, a special vector selection method is introduced and the concept of virtual vector is developed. By using the proposed PWM strategy, a MRAS speed sensor-less DTC drive can be achieved without sensing the neutral-point voltage, The strategy can be verified by simulation and experimental results.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.443-447
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• 2001

In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Reference Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach. The structure of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.777-780
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• 1991

The practical implementation of model reference adaptive systems(MRAS) using digital computer requires the derivation of discrete-time adaptation laws. This is specially important in the case of direct driver robot and light weight manipulator where inertia changes ang gravity effects are significant. We develope a discrete-time model reference adaptive control scheme for trajectory tracking of robot manipulator. Instead of the conventional Lyapunov approach hyperstabillty theory is more appealing than the Lyapunov approach. It is better suited to discrete time systems and offers more flexibility in design by providing additional free design parameters.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.12
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• pp.908-917
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• 1987

Most of moving targets are modelled as nonlinear dynamic equations. In recent years, the extended Kalman filter is frequently used for estimating their behaviors. The conditional Gaussian filter is more suitable than extended kalman filter in the filtering problem of nonlinear systems. But extended Kalman filter and conditional Gaussian filter often do not give optimal estimates and fail to track target trajectories because of its properties. Therefore it is desirable to use adaptive techniques to adapt target maneuvers. In this paper, we will discuss adaptive filtering technique using innovation process based on extended Kalman filter in real time, and suggest another maneuver estimation method using MRAS technique.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.576-578
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• 1999

본 연구의 목적은 자계방향 기준 벡터제어 이론에 기초하여 속도 센스리스 벡터제어를 구현하는 것이다. 속도센스리스 벡터제어에서 속도추정 방법은 관측기에서 얻은 상태량을 취하는 MRAS 방법이 제안되고 있지만 이득정수의 조정을 행하여야 하는 결점을 가지고 있다. 본 논문에서는 속도추정은 관측기 이론에 기초하여 2차자속 관측기와 전류센스에서 검출한 전류 값으로 행하는 새로운 속도 추정법을 이용한 제어 알고리즘을 제안한다. 그리고 제안한 방법이 본 연구에 있어서 사용한 자계방향 벡터제어시스템의 실현에 가능성이 있음을 시뮬레이션으로 검토하고 실제로 시스템을 구현하여 센스리스 속도제어를 달성하였다.

• Proceedings of the KIEE Conference
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• 2004.07d
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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.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.11-16
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• 1998

In this paper, simultaneous estimation of rotor speed and time constant for a voltage source inverter (VSI) fed induction motor drive are disccussed. The theory is based on the Model Reference Adaptive System (MRAS). The identifier executes Simultaneous rotor speed and time constant so that vector control of the induction may be achieved in the rotor-flux oriented reference frame. Furthermore, to eliminate the offset error caused by the change in the stator resistance, a fuzzy resistance regulator is also designed which operates in parallel with the rotor speed and time constant identifier

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.213-216
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• 2002

This paper describes a new approach to estimate induction motor speed from terminal voltages and currents for speed-sensorless vector control. This algorithm is based on Model Reference Adaptive System(MRAS). The proposed technique is simple and robust to the variation of motor parameters. Specially, this algorithm is not affected by the variation of stator resistance and it does not require any pure integration at all. The validity of this new approach is proved by simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.230-230
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• 2000

This paper describes a model reference adaptive system(MRAS) for speed control of vector-controlled induction motor without a speed sensor. The proposed approach is based on observing the instantaneous torque. The real torque is calculated by sensing stator current and estimated torque is calculated by stator current that is calculated by using estimated rotor speed. The speed estimation error is linearly proportional to error between real torque and estimated torque. The proposed feedback loop has linear component. Furthermore proposed method is robust to parameters variation. The effectiveness is verified by equation and simulation

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.2008-2011
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• 1998

When the vector control, which does not need a speed signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. This paper describes a rotor speed identification method of induction motor based on the theory of Model Reference Adaptive System(MRAS). The identifier execute the rotor speed identification so that the vector control of the induc-tion motor may be achieved. The improved auxiliary variable are introduce to perform accurate rotor speed identification. Simulation and experimental result show the validity of the proposed control method.