• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.795-798
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• 1991

The hybrid positon/force control is required when two or more robots perform a coorperative task in a uncertain environment, or when single robot does a task with a constant force to the environment. In this paper, a new control algorithm which control simultaneously the position and the force are proposed, however, especially the conventional position controller employed in the present robot control is used. Moreover, in order to improve the output response characteristics of the system, the PI gains which were computed from the PI gain tunning techniques, are varied based on the results of the Fuzzy algorithm.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1097-1098
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• 2011

This paper proposes high performance control of induction motor drive using fuzzy neural network precompensation PI(FNPPI) controller. To apply industrial processes, control methods is requested technique that can be demonstrate high performance and robust about load disturbance, parameter variation and uncertainty of model, etc. The PI controller dose not show satisfactory performance due to fixed gain. Therefore, this paper proposes FNPPI which is adjusted input values of PI controller according to operating conditions of motor by FNN controller mixed neural network and fuzzy. And this paper proves validity of proposed control algorithm through result analysis.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.233-235
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• 2005

Non-contact power supply (NCPS), as a clean and safe energy supply concept has been applying wildly. Comparing with the conventional transformer the non-contact transformer has a large air gap between the long primary winding and the secondary winding. Due to it, the non-contact transformer has increased leakage inductance and reduced magnetizing inductance. So the high frequency series resonant converter has been widly used on the non-contact power supply system for transferring the primary power to the secondary one, from what a high influence voltage can be gained on the secondry coil even though the large air gap exists. However, it still has the disadvantages of the load sensitive voltage gain characteristics when load is changing. In this paper, we propose a fuzzy logic controller to adjust the frequency of the inverter to track the resonat which is changing when the load is change.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.17-20
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• 2005

In this work, we compared several feature selection methods in the field of spam mail filtering. The proposed fuzzy inference method outperforms information gain and chi squared test methods as a feature selection method in terms of error rate. In the case of junk mails, since the mail body has little text information, it provides insufficient hints to distinguish spam mails from legitimate ones. To address this problem, we follow hyperlinks contained in the email body, fetch contents of a remote web page, and extract hints from both original email body and fetched web pages. A two-phase approach is applied to filter spam mails in which definite hint is used first, and then less definite textual information is used. In our experiment, the proposed two-phase method achieved an improvement of recall by 32.4% on the average over the $1^{st}$ phase or the $2^{nd}$ phase only works.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.530-532
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• 1999

In adaptive fuzzy control, system designer develops an adaptive law for the output of the unknown plant to track a given signal. The adaptation gains of the adaptive law are critical elements in the overall system, however, they were used to be selected by the designer's experience or intuition. In this paper, genetic algorithm is used to search an optimal adaptation gain and simulation results will be presented to show the improved tracking responses.

• 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.

• Proceedings of the KIEE Conference
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• 1999.11a
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• pp.28-30
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• 1999

This paper proposes a robust FPID(Fuzzy Proportional Integral Derivative) controller for the LFC(load frequency control) of 2-area power system. The PID gain parameters of the proposed robust FPID controller are self-tuned by PSGM(Product Sum Gravity Method) which is very similiar to human's inference procedures. As the results of simulation, the proposed FPID controller against various load disturbances shows that it is superior to the conventional control techniques such as optimal, PID and fuzzy control in the response characteristics of frequency and tie line power flow.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.223-225
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• 2002

In this paper, we designed fuzzy legit controller(FLC) for HVDC current control using genetic algorithm. The proposed method was applied to HVDC power system simulator in Korea Electrotechnology Research Institute(KERI). We are adjusted input/output gain of FLC by real-time using genetic algorithm. Experimental results show that FLC has the better control performance than PI controller in terms of settling time, rising time.

• Journal of the Optical Society of Korea
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• v.17 no.3
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• pp.237-241
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• 2013

This paper presents an efficient evolutionary method to optimize the gain ripple of multi-pumps photonic crystal fiber Raman amplifier using the Fuzzy Adaptive Modified PSO (FAMPSO) algorithm. The original PSO has difficulties in premature convergence, performance and the diversity loss in optimization as well as appropriate tuning of its parameters. The feasibility and effectiveness of the proposed hybrid algorithm is demonstrated and results are compared with the PSO algorithm. It is shown that FAMPSO has a high quality solution, superior convergence characteristics and shorter computation time.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.173-179
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• 2000

While a cutting tool is machining a workpiece at various cutting depth, the feedrate is usually selected based on the maximum depth of cut. Even if this selection can avoid power saturation or tool breakage, it is very conservative compared to the capacity of the machine tools and can reduce the productivity significantly. Many adaptive control techniques that can adjust the feedrate to maintain the constant cutting force have been reported. However, these controllers are not very widely used in manufacturing industry because of the limitations in measuring the cutting force signals. In this paper, turning force control systems based on the estimated cutting force signals are proposed. A synthesized cutting force monitor is introduced to estimate the cutting force as accurately as a dynamometer does. Three control strategies of PI, adaptive and fuzzy logic controllers are applied to investigate the feasibility of utilizing the estimated cutting force fur turning force control. The experimental results demonstrate that the proposed systems can be easily realized in CNC lathe with requiring little additional hardware.