• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.174-176
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• 2003

This paper considers the application of Fuzzy Logic to Smart Decision process of Smart Sensor system that interprets and response to the change of environmental parameters. The considered system consists of three sensors: temperature sensor, humidity sensor and pressure sensor. The smartness of system is constituted by the applying of Fuzzy Logic. The paper discusses the technical details of the application of Fuzzy Logic for making the system to be smarter.

• Proceedings of the KIEE Conference
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• 2001.07e
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• pp.58-61
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• 2001

The purpose of this paper is a fuzzy logic controller for XY positioning system. The overall control system consists of three parts, the position controller, the speed controller, the fuzzy logic controller. Precise tracking is achieved by fuzzy logic controller. In practice, such systems contain many uncertainties. Therefore, the XY positioning system must receive and evaluate the motion of all axis for a better contouring accuracy. Cross coupled controller utilizes all axis position error information simultaneously to produce accurate contours. However, the existing Cross coupled controllers cannot overcome friction, backlash and parameter variation. So, we propose a fuzzy logic controller of XY positioning system. Experimental results show that the proposed fuzzy logic controller is effective to improve the contouring accuracy of XY positioning system.

• Journal of the Korean Institute of Navigation
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• v.8 no.1
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• pp.15-42
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• 1984

Many studies have been done in the field of fuzzy logic theory, but it's application to the ship's steering system is few until this date. This paper is to survey the effect of application of fuzzy logic control by new compositional rule of Inference to the ship's steering system. The controller is made up of a set of Linguistic Control Rules which are conditional linguistic statements connecting the inputs and output, and take the inputs derived from deviation angle and it's angular velocity. The Linguistic Control Rules are implemented on the digital computer to verify the performance of the fuzzy logic controller and simulations have been done in six cases of initial condition and disturbance type. Consequently, it was proved that the ship's steering system by introducing the F.L.C. is performed efficiently and less energy loss system compared with the conventional autopilot.

• Journal of Electrical Engineering and Technology
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• v.5 no.3
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• pp.503-510
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• 2010

This paper proposes the use of fuzzy applications to a 4-machine and 10-bus system to check stability in open conditions. Fuzzy controllers and the excitation of a synchronous generator are added. Power system stabilizers (PSSs) are added to the excitation system to enhance damping during low frequency oscillations. A fuzzy logic power system stabilizer (PSS) for stability enhancement of a multi-machine power system is also presented. To attain stability enhancement, speed deviation ($\Delta\omega$) and acceleration ($\Delta\varpi$) of the Kota Thermal synchronous generator rotor are taken as inputs to the fuzzy logic controller. These variables have significant effects on the damping of generator shaft mechanical oscillations. The stabilizing signals are computed using fuzzy membership functions that are dependent on these variables. The performance of the fuzzy logic PSS is compared with the open power system, after which the simulations are tested under different operating conditions and changes in reference voltage. The simulation results are quite encouraging and satisfactory. Similarly, the system is tested for the different defuzzification methods, and based on the results, the centroid method elicits the best possible system response.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.89-118
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• 1996

The development and implementation of a real-time, traffic adaptive control scheme based on fuzzy logic through Video Image Detector systems (VIDs) is presented. Through VIDs based image processing, fuzzy logic can be used for a real-time traffic adaptive signal control scheme. Fuzzy control logic allows linguistic and inexact traffic data to be manipulated as a useful tool in designing signal timing plans. The fuzzy logic has the ability to comprehend linguistic instructions and to generate control strategy based on a priori verbal communication. The implementation of fuzzy logic controller for a traffic network is introduced. Comparisons are made between implementations of the fuzzy logic controller and the actuated controller in an isolated intersection. The results obtained from the application of the fuzzy logic controller are also compared with those corresponding to a pretimed controller for the coordinated intersections. Simulation results from the comparisons indicate the performance of the system is between under the fuzzy logic controller. Integration of the aforementioned schemes into and ATMS framework will lead to real-time adjustment of the traffic control signals, resulting in significant reduction in traffic congestion.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.577-582
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• 1999

Using a sole input variable simplifies the design process for the fuzzy logic controller(FLC). This is called single-input fuzzy logic controller(SFLC). However it is still deficient in the capability of adapting to the varying operating conditions. We here design a single-input adaptive fuzzy logic controller(AFLC) using a switching function of the sliding mode control. The AFLC can directly incorporate linguistic fuzzy control rules into the controller. Hence some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules can be adjusted by an adaptive law. In the proposed AFLC center values of fuzzy sets are directly adjusted by a fuzzy logic system. We prove that 1) its closed-loop system is globally stable in the sense that all signals involved are bounded and 2)its tracking error converges to zero asymptotically. We perform computer simulation using a nonlinear plant.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.493-495
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• 1998

Robust design is one method to make manufacturing less sensitive to manufacturing process. Also it is cost effective technique to improve the quality process. This method uses statistically planned experiments to vary settings of important process control parameters. In this paper we apply fuzzy optimization and fuzzy logic system to robust design concept. First a method which uses fuzzy optimization in obtaining optimum settings by measured data from experiments will be presented. Second, fuzzy logic system is made to reduce experiments using experiments results consisted with key control parameter combinations. Then optimum parameter set points are obtained by the descrebed first fuzzy optimization method after prediction the results of each parameter combinations considering each control parameter variations by nonsingleton fuzzy logic system concept.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.471-478
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• 2011

This paper proposes a method of maximum power point tracking (MPPT) using fuzzy logic control for grid-connected photovoltaic systems (PV). First, for the purpose of comparison, because of its proven and good performances, the incremental conductance (IncCond) technique is briefly introduced. A double fuzzy logic controller (DFLC) based MPPT is then proposed which has shown better performances compared to the IncCond MPPT based approach. Modeling and Simulation in grid-connected PV system results are provided for both controllers under same atmospheric condition based PSCAD/EMTDC. The double fuzzy logic MPPT controller is then simulated and evaluated, which has shown better performances.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1879_1880
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• 2009

본 논문에서는 제어상황에 따라 Type-1 Fuzzy Logic Controller가 선택적으로 rule을 사용하도록 rule 선택 알고리즘을 제안 한다. 그리고 이를 통해 연산 효율성을 높이는 방법에 관해 논한다. Type-1 Fuzzy Logic Controller는 기존의 제어기에 비해 설계하기 쉽고 성능이 더 뛰어나다. 그러나 제어 변수가 많아질수록 rule의 개수가 늘어나 연산량이 증가하게 된다. 연산량이 많아지면 고성능의 컴퓨터에서는 실시간 연산에 문제가 없으나 산업용 micro controller에서는 실시간 연산을 구현하는데 한계가 발생한다. 본 논문에서는 Type-1 Fuzzy Logic System의 논리구조에 근거하여 Type-1 Fuzzy Logic Controller의 연산량을 감소시킬 수 있는 알고리즘을 제안한다. 제안한 알고리즘은 제어상황에 따라 필요한 rule들만 선택적으로 제어값 도출을 위한 연산에 관여하도록 한다. Matlab 시뮬레이션을 통해 제안한 알고리즘의 유용성과 연산량을 실험하였다. 실험대상은 2륜 이동로봇으로 하였고 step 응답과 전/후진 시 결과를 관찰하였다. 실험 결과 제안한 알고리즘이 기존의 Type-1 Fuzzy Logic Controller에 비해 제어상황에 따라 필요한 rule들만 선택적으로 사용하는 것을 확인하였다. 결과적으로 연산 효율성이 향상되었다.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.897-900
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• 1998

Through fuzzy logic controller is very useful to many areas, it is difficult to build up the rule-base by experience and trial-error. So, effective self-tuning fuzzy controller for the position control of ball and beam is designed. In this paper, we developed the neural network control system with fuzzy-neuron which conducts the adjustment process for the parameters to satisfy have nonlinear property of the ball and beam system. The proposed algorithm is based on a fuzzy logic control system using a neural network learinign algorithm which is a back-propagation algorithm. This system learn membership functions with input variables. The purpose of the design is to control the position of the ball along the track by manipulating the angualr position of the serve. As a result, it is concluded that the neural network control system with fuzzy-neuron is more effective than the conventional fuzzy system.