• 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 Electrical Engineering and Technology
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• v.10 no.5
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• pp.2170-2178
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• 2015

This paper presents the effective and reliable speed control of PMDC motors under variable loads and reference speeds. As is known DC motors are more preferred in industrial practices. This is that, the PMDC motors don’t require brush and commutator care and to increase in torque per motor depending on developments in power electronics. In this study, proportional-integral controller (PI) and fuzzy logic controller (FL) have been designed for speed control of PMDC motor. In the design of these controllers, characteristics such as minimum overrun time, response time to the load, settling time and ideal rise time have been taken into consideration for better stability performance. In this design, the best system response was searched by examining the effect of different defuzzification methods onto the fuzzy logic system response. In conclusion, it has been seen that FL controller has a better performance for variable speed-load control of PMDC motor compared to PI controller.

• 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.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.188-199
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• 2014

Although the fuzzy logic controller is superior to the proportional integral derivative (PID) controller in motor control, the gain tuning of the fuzzy logic controller is more complicated than that of the PID controller. Using mathematical analysis of the proportional derivative (PD) and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller that has the same characteristics as the PD controller in the beginning. Then a design method of a fuzzy logic controller was proposed that has superior performance to the PD controller. This fuzzy logic controller was designed by changing the envelope of the input of the of the fuzzy logic controller to nonlinear, because the fuzzy logic controller has more degree of freedom to select the control gain than the PD controller. By designing the fuzzy logic controller using the proposed method, it simplified the design of fuzzy logic controller, and it simplified the comparison of these two controllers.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.9
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• pp.24-30
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• 2009

This paper is proposed by fuzzy-based MPPT control of photovoltaic to drive induction motor. Design and prototype implement of a fuzzy logic(FL) controller for maximum power extraction from a stand-alon photovoltaic. Error and the change of error between maximum power and real power are used by input of fuzzy controller. Moreover, it output changing of voltage from control constant. The validity of this paper is proved by comparing maximum power point tracking and performance of motor drive through comparison fuzzy and PI of tradition method.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.6
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• pp.534-542
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• 2005

This paper proposes the fuzzy logic based vector control method for a Surface Mounted Permanent Magnet Synchronous Motor(SMPMSM) used in the elevators. The gain of a conventional PI speed controller in the elevator drive system can not be usually set high due to mechanical resonances, therefore its performance becomes deteriorated. There have been many methods to solve above problems such as an acceleration feedback in the speed controller. However, the above methods have defects that parameter information is demanded. In this paper', a Fuzzy controller(FC) is adopted in the elevator drive system. The performance of a fuzzy controller is compared with a PI controller in the no load and load conditions by simulation and experiments.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1111-1113
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• 2003

This paper proposes an effective self-turning algorithm based on Artificial Neural Network (ANN) for fuzzy speed control of the indirect vector controlled induction motor. Indirect vector control method divides and controls stator current by the flux and the torque producing current so that the dynamic characteristic of induction motor may be superior. However, if motor parameter changes, the flux current and the torque producing one's coupling happens and deteriorates the dynamic characteristic. The fuzzy speed controller of an induction motor has the robustness over the effect of this parameter variation than a conventional PI speed controller in some degree. This paper improves its adaptability by adding the self-tuning mechanism to the fuzzy controller. For tracking the speed command, its membership functions are adjusted using ANN adaptation mechanism. This adaptability could be embodied by moving the center positions of the membership functions. Proposed self-tuning method has wide adaptability than existent fuzzy controller or PI controller and is proved robust about parameter variation through Matlab/Simulink simulation.

• Smart Structures and Systems
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• v.29 no.4
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• pp.617-624
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• 2022

A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.

• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.729-742
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• 2019

Natural disasters such as floods has been increased in many parts of the world, also Korea is no exception. The biggest part of natural damage in South Korea was caused by the flooding during the rainy season in every summer. The existing flood vulnerability analysis cannot explain the reality because of the repeated changes in topography. Therefore, it is necessary to calculate a new flood vulnerability index in accordance with the changed terrain and socio-economic environment. The priority of the investment for the flood prevention and mitigation has to be determined using the new flood vulnerability index. Total 25 urban districts in Seoul were selected as the study area. Flood vulnerability factors were developed using Pressure-State-Response (PSR) structures. The Pressure Index (PI) includes nine factors such as population density and number of vehicles, and so on. Four factors such as damage of public facilities, etc. for the Status Index (SI) were selected. Finally, seven factors for Response Index (RI) were selected such as the number of evacuation facilities and financial independence, etc. The weights of factors were calculated using AHP method and Fuzzy AHP to implement the uncertainties in the decision making process. As a result, PI and RI were changed, but the ranks in PI and RI were not be changed significantly. However, SI were changed significanlty in terms of the weight method. Flood vulnerability index using Fuzzy AHP shows less vulnerability index in Southern part of Han river. This would be the reason that cost of flood mitigation, number of government workers and Financial self-reliance are high.