• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.233-243
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• 1994

Generally, fuzzy PI controller that regulates the gains using fuzzy algorithm shows high performance in speed response. However, it has some problems to the load inertia variation, because the change of speed error(CE) is in a fixed range. As load inertia increases, CE is decreased and the usuage of fuzzy table is limited. Therefore, the output of the fuzzy controller has a limited range. This paper proposes an improved fuzzy PI controller. To reduce the speed overshoot, we adapt a control method that selects a proper CE range with respect to the load inertia variation. The proposed controller is applied to the vector controlled system with 2.2kW induction motor. Some simulation and experimental results are exhibited. With these results, we can easily find that proposed PI controller is more robust than the conventional fuzzy PI controller against the load inertia variation.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.163-169
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• 2003

This study was carried out develope a motor power change speed device of motor by used micro- controller. This system was producted a auto-change speed device which switching frequency was 1,000MHz by used a auto- controller. It had a continuous output current such as 5A, 11A, 25A, 35A, 50A. It used a variable voltage from 9V to 18V(Maximum). We designed hardware of and software of micro-controller, we are made up of a auto cut-off function by 3.7V for detected power-loss prevention.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.8
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• pp.126-133
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• 2000

This paper is a study on robust PID controller tuning technique using the frequency region model matching method.To design the robust PID controller satisfying disturbance attenuation and robust tracking property for a reference input first an {{{{ETA _$\infty$}}}} controller satisfying given performances is designed using an H$_{\infty}$ control method, And then the parameters(proportional gain integral gain and derivation gain) of the robust PID controller with the performances of the desinged H$_{\infty}$ controller are determined using the model matching method at frequency domain. in this paper this PID controller tuning technique is applied to PID speed controller design for BLDC motors. Consequently simulation results show that the proposed PID speed controller satisfies load torque disturbance attenuation and robust tracking property and this study has usefulness and applicability for the speed control system; design of BLDC motors.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.390-393
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• 1999

For high performance ac drives, the speed sensorless vector control and a speed control algorithm base on the Fuzzy PI controller have received increasing attention. A Fuzzy PI controller is used for robust and fast speed control and space vector modulation method is used for PWM wave generation in this proposed system. The computer simulation results show that the proposed controller are more excellent control characteristics than conventional PI controller in transient-state response.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.230-233
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• 1998

The conventional PI controller are fragile in parameter variation and load-variation. Therefore, in this paper, a speed control algorithm based on the Fuzzy PI controller is proposed for the high performance speed control of a voltage-source inverter to drive 3-phase induction motors. The computer simulation results show that the proposed controller are more excellent control characteristics than conventional PI controller in transient-state and steady-state response.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.994-997
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• 2003

This Paper presents a study of the performance of a DC servo motor with a model reference adaptive fuzzy speed controller (MRAFSC) in the presences of load disturbances. MRAFSC comprised inner feedback loop consisting of the fuzzy logic controller (FLC) and plant, and outer loop consisting of an adaptation mechanism which is designed for tuning a control rule of the FLC. Experimental results show the good performance in the DC servo motor system with the proposed adaptive fuzzy controller.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.3
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• pp.138-143
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• 2011

Electric locomotive is adapted to high speed driving and mass transportation due to obtaining high traction force. The electric locomotive is operated by motor blocks and traction motors. Train speed is controlled by suppling power from motor blocks to traction motors according to reference speed. Speed control of the electric locomotive is efficient by spending energy between motor blocks and traction motors. Currently, switched reluctance motors have been studied because the efficient is higher than induction motors. In this paper, model of the switched reluctance motor is presented and the PID controller is applied to the model for the speed control by using Simulink. Asymmetry converter is used for real-time control and system performance is demonstrated by simulating the speed of switched reluctance motor including PID controller.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.225-227
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed artificial intelligent-PI(AIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.5
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• pp.22-33
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• 2011

An induction motor operated with a conventional direct self controller(DSC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic controller(FLC) is used in conjection with DSC to minimize these problems. A FLC chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determinated by observing the vector diagram of flux and currents. This paper proposes hybrid fuzzy controller for direct torque control(DTC) of induction motor drives. The speed controller is based on adaptive fuzzy learning controller(AFLC), which provide high dynamics performances both in transient and steady state response. Flux position, error in flux magnitude and error in torque are used as FLC state variables. The speed is estimated with model reference adaptive system(MRAS) based on artificial neural network(ANN) trained on-line by a back-propagation algorithm. This paper is controlled speed using hybrid fuzzy controller(HFC) and estimation of speed using ANN. The performance of the proposed induction motor drive with HFC controller and ANN is verified by analysis results at various operation conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.366-371
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• 2014

The neural network pitch controller using changing rate of generator speed has been suggested in this paper to regulate wind turbine power above the rated wind speed. The changing rate of generator speed is used in the suggested pitch controller as well as the difference between the rated and current generator speed. Matlab/simulink has been used for simulations and it has been shown that the suggested pitch controller regulates generator speed as the rated speed of 122.9[rad/s].