• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1456-1470
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• 2017

This paper presents sensorless vector control of induction motor drives with an improved model reference adaptive system observer for rotor speed estimation and parameters identification from measured stator currents, stator voltages and estimated rotor fluxes. The aim of the proposed sensorless control method is to compensate simultaneously stator resistance and rotor time constant variations which are subject of large changes during operation. PI controllers have been used in the model reference adaptive system adaptation mechanism and in the closed loops of speed and currents regulation. The stability of the proposed observer is proved by the Lyapunov's theorem and its feasibility is verified by experimentation. The experimental results are obtained with an 1 kW induction motor using Matlab/Simulink and a dSPACE system with DS1104 controller board showing the effectiveness of the proposed approach in terms of dynamic performance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1239-1244
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• 2004

Precise positioning is an important problem facing motion control systems which usually use electric motor. A motor possesses a nonlinear property which degrades the positioning accuracy. Therefore, a compensator which linearizes the relationship between the angular velocity and input signal of the motor is required to enable precise positioning. In this paper, the design of a Model Reference Adaptive Control System (MRACS) for realizing the precise positioning for a system using a motor including the nonlinear property is described. The designed MRACS is applied to the attitude control problem on a satellite using a DC servomotor to drive its reaction wheel. Experimental results demonstrate the validity of a proposed control method for a positioning control system with an electric motor.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.570-572
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• 2005

This paper is proposed adaptive hybrid artificial intelligent(HAI) controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network(FNN) controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.143-146
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for speed control of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.873-881
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• 2014

Speed sensorless modes of operation are becoming standard solution in the area of electric drives. This paper presents flux estimator and speed estimator for the speed sensorless vector control of induction motors. The proposed sensorless methods are based on the model reference adaptive system (MRAS) observer and adaptive speed observer (ASO). The proposed speed estimation algorithm can be employed in the power control of grid connected induction generator for wind power applications. Two proposed schemes are verified through computer simulation PSIM and compared their simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.148.5-148
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• 2001

In this report, an adaptive flight control law based on a linear-parameter-varying (LPV) model is presented for a flight control system. The control system is designed to track an output of a vehicle to a reference signal from the guidance system, which generates a reference flight path. The proposed adaptive control law adjusts the controller gains continuously on line as flight conditions change. The obtained adaptive controller guarantees global stability over a wide flight envelope. Computer simulation involving six-degree-of-freedom nonlinear flight dynamics is applied to Japan´s automatic landing flight experimental vehicle (ALFLEX) to examine the effectiveness of the proposed adaptive flight control law.

• 대한전자공학회논문지
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• 제20권1호
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• pp.37-44
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• 1983

본 논문에서는 MRAC 방식을 이용하여 이산 시간이고 잡음이 없는 단일한 입출력을 갖는 선형계에 직접제어 방식으로 적응 제어 알고리즘을 원용하였다. 직접 제어 방식에서 제어기는 매개변수형으로 구성되고 그리고 매개변수 조정을 위한 검증 알고리즘은 일련의 축차방정식으로 주어지는데 이는 가중 최소 자승법에 따라 유도되었다. 가중 최소 자승법으로 제어기 매개변수를 검증했을 때 출력 추적오차가 영에 수검하는 속도가 경도법 또는 최소 자승법을 사용했을 때보다 빠르다는 것이 컴퓨터 시뮬레이견으로 확인되었으며 또한 λ를 변화시키는 제안된 가중 최소 자승법은 규범형 모델 입력의 동파수 성분에 관계언이 사용될 수 있음을 보였다. 또한 이런 경우에 있어서 수험성과 안정도에 관해서도 고찰했다.

• 대한기계학회논문집A
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• 제28권8호
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• pp.1152-1158
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• 2004

In this study a MRAC(model reference adaptive control) for fluid power elevator model system was designed. The MRAC was compared with PI control in case of applying to the elevator model system with constant external load and changing external load. In this case external load was produced by a single fluid power cylinder combined with pressure control valve. In conclusion the MRAC control performance was better than PI control performance because overshoot and steady state error of the elevator model system controlled by the MRAC were not appeared for constant and changing external load.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제48권3호
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• pp.124-130
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• 1999

Speed and position sensors require the additional mounting space, reduce the reliability in harsh environments and increase the cost of motor. Various control algorithms have been proposed for the elimination of speed senor. This paper investigates a novel speed sensorless control of induction motor. The proposed control strategy is based on MRAS(Model Reference Adaptive System) using state observer as a reference model for flux estimation. This algorithm may overcome several shortages of conventional MRAS: integrator problems, small EMF at low speed and relatively large sensitivity to resistance variation. The proposed algorithm is verified through simulation and experiment.

• 전기학회논문지
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• 제56권1호
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• pp.183-187
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• 2007

This paper proposes Fuzzy Speed Estimator using Fuzzy Logic Controller(FLC) as a adaptive law in Model Reference Adaptive System(MRAS) in order to realize the speed-sensorless control of an induction motor. Fuzzy Speed Estimator estimates the speed of an induction motor with a rotor flux of the reference model and the adjustable model in MRAS. Fuzzy logic controller reduces the error of the rotor flux between the reference model and the adjustable model using the error and the change of error of the rotor flux as the input of FLC. The experiment is executed to verify the propriety and the effectiveness of the proposed speed estimator.