• 한국지능시스템학회논문지
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• 제5권2호
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• pp.3-12
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• 1995

A controller utilizing fuzzy logic is developed to control the speed of a motor in a washing machine by choosing an appropriate phase. Due to the hardship imposed on obtaining a result from a relation established for inputs, present speed and present rate of speed, and ouput, a phase, of the system that can be tested against an experimental result, it is impossible to apply a genetic algorithm to fine-tune the fuzzy logic controller. To avoid this difficulty, a proper assumption that the parameters of an if-part of a primary fuzzy logic controller have a functional relationship with an error between computed values and experimental ones in made. Setting up of a fuzzy relationship between the parameters and the errors is then achieved through experimentally obtained data. Genetic Algorithm is then applied to this secondary fuzzy logic controller to verify the fuzzy logic. In the verification process, the primary fuzzy logic controller is used in obtaining experimental results. In this way the kind of difficulty in obtaining enough experimental values used to verify the fuzzy logic with genetic algorithm is gotten around. Selection of the parameters that would produce the least error when using the secondary fuzzy logic controller is done with applying genetic algorithm to the then-part of the controller. In doing so the optimal values for the parameters of the if-part of the primary fuzzy logic controller are assumed to be contained. The experimental result presented in the paper validates the assumption.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권1호
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• pp.7-12
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• 2005

This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper. The expert system which introduces fuzzy logic in order to process uncertainties is called fuzzy expert system. The fuzzy expert system, however, has a potential problem which may lead to inappropriate results due to the ignorance of some information by applying fuzzy logic in reasoning process in addition to the knowledge acquisition problem. In order to overcome these problems, We construct fuzzy inference network by extending the concept of reasoning network in this paper. In the fuzzy inference network, the propositions which form fuzzy rules are represented by nodes. And these nodes have the truth values representing the belief values of each proposition. The logical operators between propositions of rules are represented by links. And the traditional propagation rule is modified.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.342-345
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• 1995

This paper describes the design process and the experimental results of a fuzzy logic controller to control the tip position of a fixible-link manipulator, directly driven by a AC motor, with a large payload. The joint angle fuzzy logic controller is designed without a costly nonlinear system analysis of the flexible manipulator and the AC motor drive system. The state variables for the fuzzy logic controller are joint angle, joint velocity, link deflection, and link deflection velocity. The simulation and experimental results show that the joint position control is not satisfactory when the controller is designed under the assumption of no link flexibility and that stable joint position control and link vibration suppression can be cahieved with the fuzzy logic controller suggested in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.102.4-102
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• 2002

A deadzone compensator is designed for a positioning system using fuzzy logic. The classification property of fuzzy logic systems make them a natural candidate for the rejection of errors induced by the deadzone, which has regions in which it behaves differently. A tuning algorithm is given for the fuzzy logic parameters, so that the deadzone compensation scheme becomes adaptive, guaranteeing small tracking errors and bounded parameter estimates, formal nonlinear stability proofs are given to show that the tracking error is small. The fuzzy logic deadzone compensator is implemented on a positioning system to show its efficacy. 1. Deadzone Compansation 2. XY positioning table 3. Fuzzy Logic 4. Actuator nonlinearity

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.825-829
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• 2005

This paper presents an approach for designing a fuzzy logic-based adaptive SVC damping In controller for damping low frequency power oscillations. Power systems are often subject to low Frequency electro-mechanical oscillations resulting from electrical disturbances. Generally, power system stabilizers are designed to provide damping against this kind of oscillations. Another means to achieve damping is to design supplementary damping controllers that are equipped with SVC. Various approaches are available for designing such controllers, many of which are based on the concepts of damping torque and others which treat the damping controller design as a generic control problem and apply various control theories on it. In our proposed approach, linear optimal controllers are designed and then a fuzzy logic tuning mechanism is constructed to generate a single control signal. The controller uses the system operating condition and a fuzzy logic signal tuner to blend the control signals generated by two linear controllers, which are designed using an optimal control method. First, we design damping controllers for the two extreme conditions; the control action for intermediate conditions is determined by the fuzzy logic tuner. The more the operating condition belongs to one of the two fuzzy sets, the stronger the contribution of the control signal from that set in the output signal. Simulation studies done on a one-machine infinite-bus and a four-machine two-area test system, show that the proposed fuzzy adaptive damping SVC controller effectively enhances the damping of low frequency oscillations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.133.2-133
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• 2001

This paper focuses on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several independent, but interacting processes running on two separate stations. By using this NCS, the network delay is analyzed to find the cause of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controllers performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice for NCS due to its robustness against parameter uncertainty.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 전력전자학술대회 논문집
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• pp.268-271
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• 2001

This paper describes the power factor control of doubly fed induction machine using fuzzy logic algorithm in wind power generation system. Under fuzzy logic control, which enables superior dynamic performance, the power factor is independently controllable by decoupled d, q rotor experimental results are presented.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.785-788
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• 1993

This paper presents the prototype framework for automated integration of CMOS current-mode fuzzy logic circuits using an intelligent module approach. The library of modules representing the standard fuzzy logic operators was built. These modules were finally used to synthesized sophisticated fuzzy logic units. Fuzzy unit designs were made based upon the results of a newel methodology of the current mirror-based fuzzy logic function synthesis. This methodology is actually incorporated into the presented framework. As an example, the membership function unit was synthesized, simulated, and the final layout was generated using the presented framework. Finally, the fuzzy logic controller unit (FLC) was generated using the proposed framework. Simulation as well as measurement results show unquestionable advantages of the proposed fuzzy logic function integration system over the classical design methodology with respect to the area, relative error and performance.

• 한국시뮬레이션학회논문지
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• 제17권3호
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• pp.9-18
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• 2008

단순히 퍼지만을 사용하여 시스템을 연동하는 경우와 퍼지로직을 같이 사용하여 침입 탐지 에이전트의 시스템 성능을 향상시키는 경우에 관한 연구로서, 블랙보드 기반의 비퍼지로직을 사용하는 경우와 블랙보드 기반의 퍼지 로직을 사용하는 경우을 비교한다. 또한 BBA를 통해 정적으로 대응하던 시스템을 향상시켜 동적 대응이 가능하게 구성하여 현실적인 시스템이 되도록 구성하였다. 대상 시스템의 성능을 평가하기 위하여 시뮬레이션을 수행하였다. 퍼지 시스템을 사용함으로써 false negative를 줄일 수 있었다. 분산 침입탐지를 위해 포함된 퍼지로직은 다양한 요소를 고려하기 때문에 침입의 성능을 높일 수 있다. 퍼지시스템을 사용하는 경우와 비 퍼지 시스템의 성능을 비교함으로써 퍼지 시스템의 성능 향상을 보이며, 이러한 비교를 통해 전체 시스템의 성능 향상을 보인다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.486-489
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• 1996

The objective of this paper is to design a force feedback controller for bilateral control of a master-slave manipulator system. In a bilateral control system, the motion of the master device is followed by the slave one, while the force applied to the slave is reflected on the master. In this paper, a fuzzy logic controllers applied to the system. Using the fuzzy logic controller, the knowledge of the system dynamics is not needed. Simulations and experimental results show the performance of the proposed controller.