• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.588-590
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• 1999

In this paper the design method of a fuzzy logic controller with a genetic algorithm is proposed. Fuzzy logic controller is based on linguistic descriptions(in the form of fuzzy IF-THEN rules) from human experts. The auto-tuning method is presented to automatically improve the output performance of controller utilizing the genetic algorithm. The GA algorithm estimates automatically the optimal values of scaling factors and membership function parameters of fuzzy control rules. Controllers are applied to the processes with time-delay and the DC servo motor. Computer simulations are conducted at the step input and the output performances are evaluated in the ITAE.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.897-899
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• 1999

This paper presents a scaling factor tuning method to improve the performance of fuzzy logic controller. Tuning rules and reasoning are utilized off-line to determine the scaling factors based on absolute value of the error and its difference. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a dc-servo motor control system. The performance of this control system is demonstrated higher than a conventional fuzzy logic controller(FLC).

• 한국기계가공학회지
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• 제18권12호
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• pp.111-116
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• 2019

With the recent acceleration of industrial technologies and active research, wearable robot technologies have been applied to various fields. To study the utility of wearable robots, basic research on kinetic mechanisms of the human body, bio-signal analysis, and system control are essential. In this study, we investigated the basic structure of a wearable system and the operating principles of a driving mechanism. The control system and supporting structure, which comprise the driving mechanism, were designed and manufactured. Motion and load analyses were performed simultaneously for the design of the kinematic drive, and the driving mechanism was constructed by analyzing walking motion. The operating conditions of the cylinder were verified by stride via driving experiments. Further, the accuracy and responsiveness of the system were confirmed by comparison with actual motion, and the system safety was validated by applying loads.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 하계학술대회 논문집
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• pp.319-323
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• 1990

VSS controller is suited for systems where the robust performances in the presence of parameter variations and disturbances are most important. The practical realization of such robust VSS algorithm using DSP ($TMS_{32020}$) is dicussed in this paper. PWH-like control signal which is produced by directly using VSS control algorithm substitutes the PWM amplifier. And the armature current is used in construction of switching function for the purpose of increasing switching frequency. In order to compensate steady state error produced by various external disturbances practical integral compensator is considered.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.229-229
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• 2000

Conventional gain-tuning methods such as Ziegler-Nickels methods, have many disadvantages that optimal control ler gain should be tuned manually. In this paper, modified PID controllers which include self-tuning characteristics are proposed. Proposed controllers automatically tune the PID gains in on-1ine using neural networks. A new learning scheme was proposed for improving learning speed in neural networks and satisfying the real time condition. In this paper, using a nonlinear mapping capability of neural networks, we derive a tuning method of PID controller based on a Back propagation(BP)method of multilayered neural networks. Simulated and experimental results show that the proposed method can give the appropriate parameters of PID controller when it is implemented to DC Motor.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.572-574
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• 1998

This paper describes design method of control system with a pre-compensator using a neural network to compensate a error signal between a reference' signal and system response. The neural network which is used here is the mixed structure and it's algorithm is a back propagation that modify coupling coefficients. Applying this method to the position control system using DC servo motor as a driver, we verify the usefulness of this method with simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.509-511
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• 1998

Design of fuzzy logic controllers encounters difficulties in the selection of optimized membership function and fuzzy rule base, which is traditionally achieved by tedious trial-and-error process. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm(GA). The controller design space is coded in base-7 strings chromosomes, where each bit gene matches the 7 discrete fuzzy value. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a do-servo motor control system. It was presented in discrete fuzzy linguistic value, and used a membership function with Gaussian curve. The performance of this control system is demonstrated higher than that of a conventional PID controller and fuzzy logic controller(FLC).

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.632-634
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• 1998

This paper presents experimental results of the fuzzy controller for DC servo motor. The fuzzy controller consists of 9 quantized levels and 25 fuzzy rules. The fine Controller is employed in the fine control mode when the value of error is between -0.03 and +0.03, whereas the coarse controller is used in the coarse control mode when the value of error is in the outside range of -0.03 and +0.03. The experimental results show that the fuzzy controller provides a better performance (lower overshoot and error) than the PID controller regardless of the load applied.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 추계종합학술대회
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• pp.380-385
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• 2001

본 논문에서는 기존의 역전파 알고리즘(Back-propagation Algorithm)의 문제점인 지역 최소점(Local Minimum point) 빠질 위험을 제거함과 동시에 학습속도(learning-speed)를 빠르게 하기 위해서 모먼팀을 갖는 PID 역전파 알고리듬(PIDBPMT: PID Back-Propagation algorithm with Momentum Term)을 제안하여 모먼텀 항을 갖는 신경망 PID 제어기를 설계하였다. 그 제어기를 D.C 서보 모터를 구동원으로 하는 위치제어계에서 적용하여 시뮬레이션으로 그 성능을 검정하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 B
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• pp.1019-1021
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• 2004

BLDCM(Brushless D.C. Motor) is widely used for industrial application because of high efficiency and high power density. Especially, in servo system and home appliance. BLDCM is very useful due to high control performance and low acoustic noise. In this paper, 2.5HP rated BLDCM controller and drive was developed for tread mill application. The prototype BLDCM has 4 poles rotor and 24 slots stator. Ferrite was used as a rotor magnet due to the cost and temperature characteristic. For the stable operation of tread mill. over current and high temperature can be detected by the DSP controller. For the commutation signal, switching patterns from the sensorless circuit and hall sensor signal are used in the DSP controller.