• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.77-78
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• 2008

This paper presents to control speed of induction motors with uncertainties. We use an adaptive backstepping controller with fuzzy neural networks(FNNs) and model reference adaptive system(MRAS) at Indirect vector control method. The adaptive backstepping controller using FNNs can control speed of induction motors even we have a minimum of information. And this controller can be used to approximate most of uncertainties which are derived from unknown motor parameters, load torque such as disturbances. MRAS estimates to rotor resistance and also can find optimal flux to minimize power losses of Induction motor. Indirect vector PI current controller is used to keep rotor flux constant without measuring or estimating the rotor flux. Simulation and experiment results are verified the effectiveness of this proposed approach.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.901-904
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• 1998

In this paper, we describes PID-neural network controller for the rotary inverted pendulum. PID control is applied to many fields but has some problems in nonlinear system due to a variation of parameter. So, we should desing the controller which is adjusted PI parameters by the neural network which is learned by backpropagation algorithm. And we show that on-line control is possible through the PID-neural network controller. The angle of the pendulum is controlled and then the position of the rotating arm is also controlled to maintain with in the set point. Measurement of the pendulum angle is obtained using a potentionmeter. The objective of the experiment is to design a PID-neural network control system that positions the arm as well as maintains the ivnerted pendulum vertical. Finally, we describe the actual experiment system and confirm the experimental results.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.95-97
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• 1997

This paper deals with design and implementation of the controller for optically guided AGV. When AGV has only three photo sensors in front of body, AGV doesn't know how much the entry angle to guide line is. In this case, it is difficult to compensate the tracking error. To make sure that the AGV does not secede the guide line in tracking, PI controller and fuzzy logic controller is proposed. The proposed controller was verified and experienced through real AGV system.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.85-89
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• 1998

A switching power stage is a very nonlinear system because it has two or more operation modes in one switching cycle. To model a switching power stage, the state space averaging method has been developed. Though it allows a unified treatment of a large variety of switching power stages, the model it yields is always very nonlinear. So, it is required to linearize the averaged model. But it is well known that a controller for a nonlinear plant designed by the linearization frequently fails in showing satisfactory control performance. Hence it is very natural to try to design a nonlinear controller for a switching power stage. In design of a switching power system, nonlinear control approaches such as adaptive control and fuzzy control have been widely studied so far. In this research, a recently developed control method, time delay control is briefly studied and a design example for a ZVS PWM half bridge converter is given. The performance of the time delay controller is compared to its conventional counterpart, PI controller by computer simulations.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.9
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• pp.26-35
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• 2010

The maximum output torque developed by the machine is dependent on the allowable current rating and maximum voltage that the inverter can supply to the machine. Therefore, to use the inverter capacity fully, it is desirable to use the control scheme considering the voltage and current limit condition, which can yield the maximum torque per ampere over the entire speed range. This controller is controlled speed and current using hybrid PI(HBPI) controller and estimation of speed using ANN. Also, this paper is proposed maximum torque control of induction motor using slip angular speed and current condition at widely speed range. The performance of the proposed induction motor drive with maximum torque control using HBPI controller is verified by analysis results at dynamic operation conditions.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.650-652
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• 2004

본 논문에서는 간접 벡터 제어 방식의 유도전동기를 위한 하이브리드 퍼지 속도제어기를 설계한다. 제안한 하이브리드 퍼지 속도제어기는 유도 전동기의 속도 응답 성능을 향상시키기 위하여 응답 상태에 따라 PI(비계적분) 제어기와 퍼지 제어기를 선택하여 사용하는 형태이다. 정상상태에서는 PI 제어기를 사용하고 속도 오차값이 크면 퍼지 제어기를 사용한다. 또한 사용된 퍼지 제어기는 퍼지 입력의 파라미터를 튜닝하여 응답 성능을 높였다. 본 논문에서 제안한 하이브리드 퍼지속도 제어기와 기존의 PI 제어기의 성능을 실험을 통하여 비교 검증한다.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.26-27
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• 2013

본 논문에서는 3상 Z-소스 PWM 정류기의 DC-link단 과도응답 특성을 개선하기 위해 PI제어기를 사용한 대신에 제어 대상에 대한 정확한 수식이 없이도 제어기 설계가 가능한 퍼지 PI제어기를 이용하였다. 제안한 퍼지 PI-제어기 기반의 PWM 정류기는 교류측 전압과 전류 센서 없이 DC-link단 전압과 전류 센서만을 이용하여 교류측 전압과 전류를 추정하였으며, 이를 PSIM 시뮬레이션을 통하여 검증 하였다.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1128-1131
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• 2003

This paper proposes a speed control system based on a fuzzy logic approach, integrated with a simple and effective adaptive algorithms. And this paper attempts to provide a thorough comparative insight into the behavior of induction motor drive with PI, direct and improved fuzzy speed controller. A indirect vector controlled induction motor is simulated under varying operating condition. The validity of the comparative results is confirmed by simulation results for induction motor drive system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.78-86
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• 2003

Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1718-1719
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• 2008

본 논문에서는 철도차량의 능동조향을 위한 고전 PI 제어기 및 퍼지 제어기를 설계하여 그 성능을 서로 비교하였다. 철도차량에서 능동조향은 곡선부 주행 시 발생되는 승차감 저하 및 차륜/레일의 마모와 소음을 줄이고, 고속주행을 위한 조향성능 및 주행안정성을 확보하기 위한 제어기술이다. 논문에서는 차량 1량을 모델로 하여 측정된 휠-레일의 횡변위(Lateral Displacement) 정보를 토대로 휠의 요모멘트를 제어하는 전략을 사용하여 제어기를 설계하였으며, 시뮬레이션을 통해 제어기 응답 특성을 비교하였다.