• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.3
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• pp.21-33
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• 1997

In this paper, a method of self-organizing for fuzzy logic controller(FLC) through learning of the proper direction of coritrol is proposed. In case of designing a self-organizing FLC for unknown dynamic plants based on the gradient descent method, it is difficult to identify the desirable direction of the change of control inpul. in which the error would be decreased. To resolve this problem, we propose a method as fo1lows:at first, assign representative values for the direction of change of error with respect to control input to each partitioned region of the states, and then, learn the fuzzy control rules using the reinforced representative values through iterative trials. 'The proposed self-organizing FLC has simple structure and it is easy to design. The validity of the proposed method is proved by the computer simulation for an inverted pendulum system.

• Proceedings of the KIEE Conference
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• 1999.07b
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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).

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.404-407
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• 1992

In this thesis, the algorithm of Fuzzy Logic Control(FLC) is applied to the Nonlinear system to implement a system response. Proportional-Integral-Derivative(PID) controller is also used to control the various systems. Look-up table is applied to decide the control input, and the other look-up table is added for saving memories and inference time. Generally, FLC input variables are error(E) and error derivative($\Delta$E). In this algorithm. another Input variable error's second derivative($\Delta^2$E) is added for Robust Fine control.

• Smart Structures and Systems
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• v.23 no.2
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• pp.155-171
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• 2019

In this study, Semi-active Tuned Mass Dampers (STMDs) are employed in order to cover the prevailing uncertainties and promote the efficiency of the Tuned Mass Dampers (TMDs) to mitigate undesirable structural vibrations. The damping ratio is determined using type-1 and type-2 Fuzzy Logic Controllers (T1 and T2 FLC) based on the response of the structure. In order to increase the efficiency of the FLC, the output membership functions are optimized using genetic algorithm. The results show that the proposed FLC can reduce the sensitivity of STMD to excitation records. The obtained results indicate the best operation for T1 FLC among the other control systems when the uncertainties are neglected. According to the irrefutable uncertainties, three supplies for these uncertainties such as time delay, sensors measurement noises and the differences between real and software model, are investigated. Considering these uncertainties, the efficiencies of T1 FLC, ground-hook velocity-based, displacement-based and TMD reduce significantly. The reduction rates for these algorithms are 12.66%, 26.43%, 20.98% and 21.77%, respectively. However, due to nonlinear behavior and considering a range of uncertainties in membership functions, T2 FLC with 7.2% reduction has robust performance against uncertainties compared to other controlling systems. Therefore, it can be used in actual applications more confidently.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.155-162
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• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance, FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and to increase efficiency. a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy PI and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and the resultant rule base is Macvicar-Whelan type. And the membership function is a Gaussian function. The frequency response information is used in tuning of the membership functions. Also a tuning strategy for the scaling factors is proposed based on the relationship between PID gain and the scaling factors. Simulation results show better performance and the effectiveness of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.12
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• pp.561-567
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• 2001

This paper describes the application of Fuzzy Logic Controller (FLC) to Thyristor Controlled Series Capacitor (TCSC) which can have significant impact on power system dynamics. The function of the FLC is to control the firing angle of the TCSC. We tuned the scaling factors of the FLC using Tabu Search. The proposed FLC is used for damping the low frequency oscillations caused by disturbances such as the sudden changes of small or large loads or the outages in the generators or transmission lines. To evaluate usefulness of the proposed FLC, we performed the computer simulation fur single-machine infinite system. The response of FLC is compared with that of PD controller optimized using Tabu Search. Simulation results that the FLC shows better control performance than PD controller.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.650-652
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• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance. FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and increase efficiency, a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy Pi and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and them. The resultant rule base is Macvicar-Whelan type. The frequency response information is used in tuning of membership functions. Also a tuning strategy for the scaling factors is Proposed based on the relationship between PID gain and them. Simulation results show better performance and the effectiveness of the proposed method.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.3
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• pp.303-312
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• 2002

In this paper, a fuzzy logic controller(FLC) for parallel operation system of PWM converters with high performances is proposed and a PI controller is also realized to compare with the performances of the proposed FLC. The simulation and experimental results show that performances of the proposed FLC are far more excellent compared with those of PI controller, especially in points of DC voltage transient response characteristics and current control transient response characteristics at step increase of rated load. To verify the superiorities of the proposed FLC and actually apply it in industrial field, Simulation iud experimental results are provided to verify the implemented a PWM converter system with 15kw capacity in paralleled with two 7.5kW PWM converters.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1400-1407
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• 2015

In the paper, we suggest bettered EHMECS(Enhanced Hybrid Multi Electrical Cupping System) to regulate automatically vacuum pressure using many cupping cup at once. We controlled accurately the pressure using S-PI control technique in pump motor to input the air inside cupping cup. S-PI control compared constant velocity, load and velocity variance between existing PI and FLC(Fuzzy Logic Control). The stabilization time of suggested S-PI control improve 20% of existing PI and 8% of FLC. The error constant of normal condition improved 71% of existing PI and 62% of FLC in steady speed and 80% of existing PI and 67% of FLC in load change. Also the error constant about velocity variance improve 45% of PI control. It is prove the suggested S-PI control technique. When use long time vacuum pressure of cupping cup regulated the suggested S-PI control technique, can loosen knotted muscles.

• Journal of Power System Engineering
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• v.22 no.1
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• pp.18-24
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• 2018

This paper focuses on systematic design about the membership ranges of the main design factors such as control error, control error rate, and sampling time for the fuzzy logic control of the variable speed drive refrigeration cycle. The upper and the lowest limit of the membership ranges are set up from the data of static characteristics obtained by experiments. Three kinds of membership ranges on the control error and the control error rate are tested by experiments. Especially, an effect of sampling time on control performance is also investigated in the same way. Experimental data showed the control error rate and the sampling time strongly effected on the control performance of the refrigeration cycle with a variable speed drive.