• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.12-17
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• 2004

This study is designed to grope for logical methods in the decision-making process of human beings such as creation and analysis. With this in mind, the paper worked with a process where the designers of a design team gather and analyze their opinions in a design process to decide on the HVAC system of buildings. The paper introduced the fuzzy theory, or one of the methods to quantitatively describe language values with ambiguous features, suggesting a method to determine the judgement and suggestion values of the HVAC designers with the characteristics of language variables as the values of design factors greatly influencing the HVAC system. As a result, the paper tested the possibility of the fuzzy system as a logical method to gather the judgement of HVAC designers in a stage of HVAC type selection exerting a great influence on the experience and judgement of the designers and having powerful linguistic features and to determine an appropriate HVAC type which can satisfy the suggested values of related design factors.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.93.1-93
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• 2001

An evolutionary approach for the design of Fuzzy Logic Systems(FLSs) is proposed. Membership functions(MFs) in Takagi-Sugeno type fuzzy logic system is optimized through evolutionary process. Output singleton values are obtained through pseudo-inverse method. The proposed technique is unique for that, to prevent overfilling phenomenon, limited-level RBF membership functions are used and the new fitness function is invented. To show the effectiveness of the proposed method, some simulations results on model identification are given.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.153-154
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• 2008

본 논문의 Type-2 TSK 퍼지 논리 시스템(Fuzzy Logic System; FLS)은 전반부 멤버쉽 함수로 가우시안 형태의 Type-2 퍼지 집합을 이용하고 후반부는 계수가 상수인 1차 선형식을 사용한다. 또한 Type-1 TSK 퍼지 논리 시스템을 Type-2 TSK 퍼지 논리 시스템으로 확장하고 제안된 모델을 가스로 공정 데이터와 sugeno 데이터에 적용한다. 여기서 인위적인 노이즈를 갖는 입력 데이터를 사용하여 제안된 모델의 성능이 기존의 모델보다 우수함을 수치적인 예로 보인다.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.141.1-141
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• 2001

This paper describes an approach for synthesizing a modularized gain scheduled PD type fuzzy logic controller(FLC) for a high maneuverable aircraft system, where the gains of FLC are on-line adapted according to the flight condition. Specially, the systematic procedure via root locus technique is carried out for the sellection of the gains of FLC. Simulation results demonstrate that the proposed gain scheduled fuzzy logic controller yields better control performance than the normal (without gain scheduling) fuzzy controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.44-49
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• 2001

For minimum phase systems, the conventional fuzzy logic controllers (FLCs) use the error and the change-of-error as fuzzy input variables. Then the control rule table is a skew symmetric type, that is, it has UNLP (Upper Negative and Lower Positive) or UPLN property. This property allowed to design a single-input FLC (SFLC) that has many advantages. But its control parameters are not automatically adjusted to the situation of the controlled plant. That is, the adaptability is still deficient. We here design a single-input direct adaptive FLC (SDAFLC). In the AFLC, some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules are adjusted by an adaptive law. The SDAFLC is designed by a stable error dynamics. We prove that its closed-loop system is globally stable in the sense that all signals involved are bounded and its tracking error converges to zero asymptotically. We perform computer simulations using a nonlinear plant and compare the control performance between the SFLC and the SDAFLC.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.972-980
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• 2010

In this study, we introduce the design methodology of an optimized type-2 fuzzy cascade controller with the aid of hierarchical fair competition-based genetic algorithm(HFCGA) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. Consequently the displacement change of the position of the moving ball and its ensuing change of the angle of the beam results in the change of the position angle of a servo motor. The type-2 fuzzy cascade controller scheme consists of the outer controller and the inner controller as two cascaded fuzzy controllers. In type-2 fuzzy logic controller(FLC) as the expanded type of type-1 fuzzy logic controller(FLC), we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. The control parameters(scaling factors) of each fuzzy controller using HFCGA which is a kind of parallel genetic algorithms(PGAs). HFCGA helps alleviate the premature convergence being generated in conventional genetic algorithms(GAs). We estimated controller characteristic parameters of optimized type-2 fuzzy cascade controller applied ball & beam system such as maximum overshoot, delay time, rise time, settling time and steady-state error. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on HFCGA, is presented in comparison with the conventional PD cascade controller based on serial genetic algorithms.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.325-328
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• 2008

본 논문에서는 비선형 모델의 설계를 위해 Type-2 퍼지 논리 집합을 이용하여 불확실성 문제를 다룬다. 퍼지 논리 시스템의 멤버쉽 함수와 규칙의 구조는 불확실성이 존재하는 언어적인 정보 또는 수치적 데이터를 바탕으로 설계된다. 기존의 Type-1 퍼지 논리 시스템은 외부의 노이즈와 같은 불확실성을 효율적으로 취급할 수 없다. 그러나 Type-2 퍼지 논리 시스템은 불확실한 정보까지 멤버쉽 함수로 표현함으로서 불확실성을 효과적으로 다룰 수 있다. 따라서 본 논문에서는 규칙의 전 ${\cdot}$ 후반부가 Type-2 퍼지 집합으로 구성된 Type-2 퍼지 논리 시스템을 설계하고 불확실성의 변화에 대한 비선형 모델의 성능을 비교한다. 여기서 규칙 전반부 멤버쉽 함수의 정점 선택은 C-means 클러스터링 알고리즘을 이용하고, 규칙 후반부 퍼지 집합의 정점 결정에는 입자 군집 최적화(PSO : Particle Swarm Optimization) 알고리즘을 사용한다. 마지막으로, 비선형 모델 평가에 대표적으로 이용되는 가스로 시계열 데이터를 제안된 모델에 적용하고, 입력 데이터에 인위적인 노이즈가 포함되었을 경우 Type-2 퍼지 논리 시스템이 기존의 Type-1 퍼지 논리 시스템보다 우수함을 보인다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.76-79
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• 2003

퍼지 로직 시스템(FLS)은 다양한 분야에서 성공적으로 사용되고 있다 퍼지 로직 시스템의 멤버십 함수와 규칙은 언어적인 정보나 수치적 데이터를 사용하여 표현된다. 또한 이러한 정보나 데이터에는 불확실성과 노이즈 등이 존재한다. 그러나 단순한 퍼지 로직 시스템으로노이즈가 포함된 불확실한 정보를 효과적으로 다루고 표현하는 데는 한계가 있다. 그러므로 노이즈가 포함된 정보를 효율적으로 처리하기 위해 본 논문에서는 type-2 FLS를 이용한다. 노이즈가 포함되어 불확실한 정도를 정확한 값으로 표현하기 어려울 때, type-2 FLS은 보다 정확하게 정보들을 다를 수 있음을 보인다. 비선형 시계열 시스템인 Box-Jenkins 데이터를 이용하여 singleton Type-1 FLS과 non-singleton type-1 FLS의 결과 값을 확인하고 이의 성능을 type-2 FLS과 비교, 분석한다.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.