• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.221-223
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• 2000

This paper describes the design of SVC fuzzy logic controller (SVC-FLC) using adaptive evolutionary algorithm and we tuned the gain of input-output variables of SYC-FLC using it. We performed the nonlinear simulation on an single-machine infinite system to prove the efficiency of the proposed method. The proposed SYC-FLC showed the better performance than PD controller in terms of the settling time and damping effect, for system operation condition used in evaluating the robustness and three phase grounding default in cases of nominal loading used in tuning SVC-FLC for a single-machine infinite system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1389-1393
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• 2011

In this paper, we implement the VLC system based on CAN communication which is usually used in car, plane, ship, product line control system, medical device and industrial device. We implement the application circuit which is VLC and CAN communication and explain the principle. Circuit's pulse features are demonstrated by each part's signal. Total communication distance is 3m and it's transmission performance is error free.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.34-36
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• 2000

This paper proposes the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gain of input-output variables of fuzzy logic controller and weights of neural network using Tabu search. Neural network used to tune the output gain of FLC adaptively. We have weights of neural network learned using back propagation algorithm. We performed the nonlinear simulation on an single-machine infinite system to prove the efficiency of the proposed method. The proposed AFLC showed the better performance than PD controller in terms of the settling time and damping effect, for power system operation condition.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.36-51
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• 1995

An approach to robot hybrid position/force control, which allows force manipulations to be realized without overshoot and overdamping while in the presence of unknown environment, is given in this paper. The manin idea is to used dynamic compensation for known robot parts and fuzzy compensation for unknown environment so as to improve system performance. The fuzzy compensation is implemented by using rule based fuzzy approach to identify the unknown environment. The establishment of proposed control system consists of following two stages. First, similar to the resovled acceleration control method, dynamic compensation and PD control based on known robot dynamics, kinematics and estimated environment stiffness is introduced. To avoid overshoot the whole control system is constructed with overdamping. In the second stage, the unknown environment stiffness is identified by using fuzzy reasoning, where the fuzzy compensation rules are obtained priori as the expression of the relationship betweenenvironment stiffness and system. Based on the simulation result, comparison between cases with or without fuzzy identifications are given, which illustrate the improvement achieced.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.5
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• pp.205-211
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• 2000

This paper presents an optimal design method for fuzzy logic controller (FLC) of HVDC using an Adaptive Evolutionary Algorithm(AEA). We have proposed the AEA which uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary algorithms. The AEA is used for tuning fuzzy membership functions and scaling constants. Simulation results show that disturbances are well damped and the dynamic performances of FLC have better responses than those of PD controller when AC system load changes suddenly.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.416-419
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• 2001

In this paper a new approach to estimate scaling factors of fuzzy controllers such as the fuzzy PID controller and the fuzzy PD controller is presented. The performance of the fuzzy controller is sensitive to the variety of scaling factors[1]. The desist procedure dwells on the use of evolutionary computing(a genetic algorithm) and estimation algorithm for dynamic systems (the inverted pendulum). The tuning of the scaling factors of the fuzzy controller is essential to the entire optimization process. And then we estimate scaling factors of the fuzzy controller by means of two types of estimation algorithms such as Neuro-Fuzzy model, and regression polynomial [7]. This method can be applied to the nonlinear system as the inverted pendulum. Numerical studies are presented and a detailed comparative analysis is also included.

• Proceedings of the KIEE Conference
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• 2000.07e
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• pp.142-146
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• 2000

In this paper, we are applied the Genetic Algorithm(GA) to design of the robust $H^{\infty}$ speed controller by auto-tuning of the weighting function. GA is used to design of the weighting functions in the robust $H^{\infty}$ controller. To evaluate the performances of the proposed robust $H^{\infty}$ controller, we make an experiment on $H^{\infty}$ speed controller of an actual DC servo- motor system with nonlinear characteristics. Experimental results show that proposed controller have better performance than those of PD controller.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.812-814
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• 1999

In this paper, we are applied the Genetic Algorithm (GA) to design of fuzzy logic controller (FLC) for a DC Servo-Motor Speed Control. GA is used to design of the membership functions and scaling factor of FLC. To evaluate the performances of the proposed FLC, we make an experiment on FLC for the speed control of an actual DC servo-motor system with nonlinear characteristics. Experimental results show that proposed controller have better performance than those of PD controller.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2467-2469
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• 1999

In this paper. the stability control system of constant output DC-DC converter is composed of considering a ripple source input and a transient variable sinusoidal power. Also, we design I-PD controller and add phase shift controller. Therefore, it is proposed controller that is stable about the input voltage and load alteration and tracking desired value.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.269-272
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• 1992

In this paper, an implementation approach of Fuzzy Position Controller for DC servo motor which requires the faster and more accurate dynamics is presented. The proposed Fuzzy position controller is consists of an adjustment routine obtaining optimal scale factors and a Fuzzy control routine inferencing optimal control signals, using 80286 microprocessor and DT 2801 board. Comparing to conventional PD controllers, the control performances such as reaching time, overshoot, disturbance adaptability and etc. are substantially improved.