• 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.

• Journal of Power Electronics
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• 제13권4호
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• pp.656-668
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• 2013

This paper presents a wavelet-fuzzy based controller for indirect field oriented control of three-phase induction motor drives. The discrete wavelet transform is used to decompose the error between the actual speed and the command speed of the induction motor drive into different frequency components. The transformed error coefficients along with the scaling gains are used for generating the control component of the motor. Self-tuning fuzzy logic is used for online tuning of the scaling gains of the controller. The proposed controller has the ability to meet the speed tracking requirements in the closed loop system. The complete indirect field oriented control scheme incorporating the proposed wavelet-fuzzy based controller is investigated theoretically and simulated under various dynamic operating conditions. The simulation results are compared with a conventional proportional integral controller and a fuzzy based controller. The speed control scheme incorporating the proposed controller is implemented in real time using a digital processor control board. Simulation and experimental results validate the effectiveness of the proposed controller.

• 전력전자학회논문지
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• 제3권2호
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• pp.138-147
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• 1998

본 논문에서는 구현이 간단하고 강인한 제어특성을 갖는 퍼지제어를 이용하여, 연속적으로 부하와 속도지령이 변하는 전기자동차 구동용 유도전동기가 부하에 무관하게 지령속도를 추종할 수 있는 제어기를 구성하고자 한다. 그리고 유도전동기를 구동하기 위한 PWM(Pulse Width Modulation)파형은 최대출력전압이 높고 디지털구현이 용이한 공간전압벡터 변조법을 이용하여 생성하였다. 제안된 시스템이 빠르고 외란에 강할 뿐만 아니라, 지령 속도에 잘 추종함을 확인할 수 있었다. 따라서 연속적으로 속도지령이 변하고 부하변동을 갖으며, 외란의 영향을 받기 쉬운 전기 자동차의 구동장치에 제안된 퍼지 제어기의 타당성을 입증하였다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2005년도 전력전자학술대회 논문집
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• pp.20-22
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• 2005

In this paper, we propose fuzzy-neural network controller that combines a fuzzy control and the Neural Networks for high performance control of induction motor drive, Also, this paper is proposed control of maximum torque per ampere of induction motor. This strategy is proposed which is simple in structure and has the honest goal of minimizing the stator current magnitude for given load torque. The performance of the proposed induction motor drive with maximum torque control using fuzzy-neural network controller is verified by simulation at dynamic operation conditions.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제51권12호
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• pp.691-696
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• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for induction motor speed control. When induction motor is continuously used long time, its electrical and mechanical Parameters will change, which degrade the Performance of PID controller considerably. This Paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using dSPACE(DS1102) board are performed to verify the effectiveness of the proposed scheme.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 학술발표 논문집
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• pp.180-185
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• 1995

In this paper, we designed the speed controller with high accuracy and speedy steady-state response, in Induction motor control system, Fuzzy P-1 controller of Induction motor using Microprocessor have an appropriate fuzzy rule matrix (which is 2-separate Look-up Table) The usefulness of proposed fuzzy P-1 controller will be confirmed by experiments which we compare with conventional P-1 controller.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권7호
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• pp.437-442
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• 2005

In order to realize the speed control of an induction motor, the information of the rotor speed is needed. So the speed sensor as an encoder or a pulse generator is used to obtain it. But the use of speed sensor occur the some problems in the control system of an induction motor. To solve the problems, the appropriate speed estimation algorithm is used instead of the speed sensor. Also there is the limitation to improve the speed control performance of an induction motor using the existing speed estimation algorithm. Therefore, in this paper, intelligent speed estimator using Fuzzy-Neural systems as adaptive laws in Model Reference Adaptive System is proposed so as to improve the existing estimation algorithm and ,using the rotor speed estimated by the Proposed estimator, the speed control of an induction motor without speed sensor is performed. The computer simulation and the experiment is executed to prove the performance of the speed control system usinu the proposed speed estimator.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 춘계종합학술대회
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• pp.713-716
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• 2007

In this paper, we consider one of robust control system, fuzzy PI+fuzzy D controller dealing with noise, load, changed parameters of plant. We apply PI+D controller with a design for output of differential function and, we plan fuzzy controller with input for PID parameter of PI+D controller so We design control system meet with the change of environment with robust in relation to change of parameter. Fuzzy control is possessed of easy 4 rules and membership function and We design fuzzy PI+fuzzy D controller. Plant of this paper make a choice of 3 phase induction motor.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권9호
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• pp.569-575
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for high performance of induction motor drive. The design of this algorithm based on 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 analysis prove that the proposed control system has strong high performance and robustness to parameter variation. and steady- state accuracy and transient response.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 전력전자학술대회 논문집
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• pp.222-224
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• 2002

This paper investigates the adaptive control of a fuzzy logic based speed and flux controller for a vector controlled induction motor drive. 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 model reference adaptive control(mAC) fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed MRAC fuzzy controller is confirmed by performance results for induction motor drive system.