• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.299-302
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• 2003

In fuzzy control systems having large volumes of fuzzy data. one of the important problems is the improvement of execution speed in the fuzzy inference and defuzzification stages. In this paper, to improve the speedup of fuzzy controllers, we use an integer line mapping algorithm to convert [0, 1] real values in the fuzzy membership functions to integer pixels. U sing this, we propose a real-time high-speed fuzzy control system and implement a fast fuzzy processor and control system using FPGAs.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.161-166
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• 2009

Condensing gas boiler units may make a big role for the reduction of energy consumption in heating industries. In order to decrease the energy consumption of a boiler unit, the effective operation is necessary. In this study, the supply water temperature algorithm of a condensing gas boiler was developed. This includes the setpoint algorithm and the control algorithm of the supply water temperature. The setpoint algorithm was developed by the fuzzy logic and the control algorithm was developed by the proportional integral algorithm. In order to analyse the performance of the supply water temperature algorithm, the dynamic model of a condensing gas boiler system was used. Simulation results showed that the supply water temperature algorithm developed for this study may be practically applied for the control of the condensing gas boiler.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.5 s.98
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• pp.104-111
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• 1999

A semi-active suspension system for a vehicle using an Electrorheological Fluid damper has been studied. Apparent viscosity of ERF(Electrorheological Fluid) can be changed rapidly by applying electric field. The damping force of ER damper can be selectively controlled by employing electric field to the ER fluid domain. This paper deals with a two-degree-of-freedom suspension using the ER damper for a quarter car model. An intelligent control method using fuzzy control with genetic algorithm has been employed to control the damping force of the ER damper. The GA designs the optimal structure and performance of Fuzzy Net Controller having hybrid structure. The designed fuzzy net controller has been compared with the skyhook type controller for a quarter car model. The computer simulation results show that the semi-active suspension with ER damper has a good performance in the sense of ride quality with less vibration for ground vehicle.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.68-70
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• 1996

A fuzzy network using genetic algorithm is investigated in the context of control for finite dimensional nonlinear discrete systems. The proposed FN(Fuzzy Network) constructed to identify various parameter of fuzzy control is used for the nonlinear system control. Each of two FN, presented FN control system is based on a framework of closed loop control. A proposed FNN model trains using the modeling error and the closed loop error. That case study shows that the presented FN model and closed loop control system is very useful in practical sense.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1565-1568
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• 1997

In this paper, a fuzzy based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy lovic is employed to express the degree of appropriateness when alternative machnies are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2959-2961
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• 1999

A position control algorithm for a inverted pendulum is studied. The proposed algorithm is based on a fuzzy theory and Generalized Radial Basis Function(GRBF). The conventional fuzzy methods need expert's knowledges or human experiences. The GRBF, which is an optimization algorithm, tunes automatically the input-output membership parameters and fuzzy rules. The simulation is presented to illustrate the approaches.

• Earthquakes and Structures
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• v.17 no.3
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• pp.307-315
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• 2019

Building prediction and control theory have been drawing the attention of many scientists over the past few years because design and control efficiency consumes the most financial and energy. In the literature, many methods have been proposed to achieve this goal by trying different control theorems, but all of these methods face some problems in correctly solving the problem. The Evolutionary Bat (EB) Algorithm is one of the recently introduced optimization methods and providing researchers to solve different types of optimization problems. This paper applies EB to the optimization of building control design. The optimized parameter is the input to the fuzzy controller, which gives the status response as an output, which in turn changes the state of the associated actuator. The novel control criterion for guarantee of the stability of the system is also derived for the demonstration in the analysis. This systematic and simplified controller design approach is the contribution for solving complex dynamic engineering system subjected to external disturbances. The experimental results show that the method achieves effective results in the design of closed-loop system. Therefore, by establishing the stability of the closed-loop system, the behavior of the closed-loop building system can be precisely predicted and stabilized.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.2
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• pp.51-60
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• 2005

In this paper, we design the GA-fuzzy precompensator of a Power System Stabilizer for Thyristor Controlled Series Capacitor(TCSC-PSS) for enhancement of power system stability. Here a fuzzy precompensator is designed as a fuzzy logic-based precompensation approach for TCSC-PSS. This scheme is easily implemented by adding a fuzzy precompensator to an existing TCSC-PSS. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Nonlinear simulation results show that the proposed control technique is superior to conventional TCSC-PSS in dynamic responses over the wide range of operating conditions and in convinced robust and reliable in view of structure.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.2
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• pp.83-92
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• 2002

In this paper, we design a GA-fuzzy precompensator for enhancement of power system stability. Here, a fuzzy prerompensator is designed as a fuzzy logic-based precompensation approach for Power System Stabilizer(PSS). This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PSS. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Simulation results show that the proposed control technique is superior to a conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.2
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• pp.310-316
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• 2003

One of the significant subject in the automatic arc welding is to establish control system of the welding parameters for controlling bead geometry as a criterion to evaluate the quality of arc welding. This paper proposes an inference algorithm for bead geometry in CMA Welding using Neuro-Fuzzy algorithm. The characteristic welding parameters are measured by the circuit composed of hall sensor, voltage divider tachometer, etc. and then the bead geometry of each weld pool is calculated and detected by an image processing with CCD camera and a measuring with microscope. The relationships between the characteristic welding parameters and the bead geometry have been arranged empirically. From the result of experiments, membership functions and fuzzy rules are tuned and determined by the learning of neural network, and then the relationship between actual bead geometry and inferred bead geometry are concluded by fuzzy logic controller. In the applied inference system of bead geometry using Neuro-Fuzzy algorithm, the inference error percent is within -5%∼+4% in case of bead width, -10%∼+10% in bead height, -5%∼+6% in bead area, -10%∼+10% in penetration. Use of the Neuro-Fuzzy algorithm allows the CMA Welding system to evaluate the quality in bead geometry in real time as the welding parameters change.