• 디지털콘텐츠학회 논문지
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• 제2권1호
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• pp.51-61
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• 2001

퍼지 제어기(FLC)는 고전적인 제어기 보다 외란에 강하고 초기치에 대한 과도응답도 우수할 뿐만 아니라 시스템의 수학적 모델과 파라메터 값을 알지 못하더라도 적절한 제어가 가능하다. 그러나 퍼지 제어기의 제어 규칙 생성은 전문가의 경험과 일단 결정된 제어 규칙은 고정됨으로 인해 제어 시스템의 환경변화에 적응할 수 없는 한계성이 있다. 또한 제어기의 출력값은 미세한 오차를 가지곤 있어 정확한 목표 값에 수렴할 수 없다. 이러한 미세한 오차를 없애기 위하여 여러 가지 방법이 연구되고 있는데, 본 논문에서는 FLC에 NN(Neural Network)과 GA(Genetic Algorithm)를 결합한 GA-FNNIC(유전알고리즘-퍼지 신경망 지능 제어기 : Genetic Algorithm - Fuzzy Neural network Intelligence Controller)를 제안한다. 제안된 GA-FNNIC와 FLC 제어기 간의 출력 특성, 수렴속도, 과도특성과 상승시간에 대해 비교 분석하고, 최종적으로 본 GA-FNNIC가 오차없이 목표치에 정확하게 수렴하는 것을 보인다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권2호
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• pp.151-157
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• 2008

A non-fragile guaranteed cost control (GCC) problem is presented for a class of discrete time-delay nonlinear systems described by Takagi-Sugeno (T-S) fuzzy model. The systems are assumed to have norm-bounded time-varying uncertainties in the matrices of state, delayed state and control gains. Sufficient conditions are first obtained which guarantee that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound. Then the design method of the non-fragile guaranteed cost controller is formulated in terms of the linear matrix inequality (LMI) approach. A numerical example is given to illustrate the effectiveness of the proposed design method.

• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.139-145
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• 2002

In Cretu (2001), triangular norms and their hierarchy are investigated. In this paper, we give new proofs which are significantly shorter than those given in Cretu, applying a known result which involves only one argument of one-place rather than two-place argument s by Klement et al.(1997).

• 제어로봇시스템학회논문지
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• 제9권5호
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• pp.374-378
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• 2003

A new discrete-time fuzzy output feedback control method for nonlinear systems with unknown time-delay is proposed. Ma et al. proposed an analysis and design method of fuzzy controller and observer and Cao et al. extend this result to be applicable fir the nonlinear systems with known time-delay. For the case of unknown time-delay, we derive the sufficient condition f3r the asymptotic stability of the equilibrium Point by applying Lyapunov-Krasovskii theorem and convert this condition into the LMI problem.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권1호
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• pp.6-9
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• 2006

A generalized net is used to construct a model which describes the process of evaluation of the problems solved by students. The model utilizes the theory of intuitionistic fuzzy sets. The model can be used to simulate some processes, related to estimation of students' background.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1317-1341
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• 2021

Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.

• 터널과지하공간
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• 제9권4호
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• pp.337-349
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• 1999

터널의 안전진단시 관련기술자들이 겪는 어려움은 터널구조물의 안전성에 미치는 다양한 영 향인자 만큼이나 많다. 때문에 안전진단의 최종결과로 대별되는 상태평가와 안전성평가에서는 터널 안전진단 전문가 또는 전문기관에서 조차 객관적인 결과을 얻어내기가 어렵다. 본 연구에서는 애매함이 산재해 있는 터널구조물의 안전진단시 겪는 여러 가지 문제들 중 콘크리트 라이닝의 상태평가를 보다 정량적이고 객관적으로 수행하기 위하여 인공지능기법 중 진단, 제어, 의사 결정 등에 효과적인 방법으로 알려진 퍼지 추론 방법을 이용하여 해결해보고자 시도하였다. 본 연구를 통해 퍼지추론을 이용한 평가시 스템인 T-FLAS를 개발하고, 기존의 터널 안전진단 결과와의 비교를 통하여, 터널 안전진단에 퍼지추론 적용 가능성을 확인 하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.480-480
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• 2000

In this paper, we proposed a fuzzy-neuro controller to control the speed of wound rotor induction motor with slip energy recovery. The speed is limited at some range of sub-synchronous speed of the rotating magnetic field. Control speed by adjusting resistance value in the rotor circuit that occurs the efficiency of power are reduced, because of the slip energy is lost when it passes through the rotor resistance. The control system is designed to maintain efficiency of motor. Recently, the emergence of artificial neural networks has made it conductive to integrate fuzzy controllers and neural models for the development of fuzzy control systems, Fuzzy-neuro controller has been designed by integrating two neural network models with a basic fuzzy logic controller. Using the back propagation algorithm, the first neural network is trained as a plant emulator and the second neural network is used as a compensator for the basic fuzzy controller to improve its performance on-line. The function of the neural network plant emulator is to provide the correct error signal at the output of the neural fuzzy compensator without the need for any mathematical modeling of the plant. The difficulty of fine-tuning the scale factors and formulating the correct control rules in a basic fuzzy controller may be reduced using the proposed scheme. The scheme is applied to the control speed of a wound rotor induction motor process. The control system is designed to maintain efficiency of motor and compensate power factor of system. That is: the proposed controller gives the controlled system by keeping the speed constant and the good transient response without overshoot can be obtained.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 춘계학술대회
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• pp.293-297
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• 1996

For the representative beat calculation and efficient rhythm analysis new method, that is, QRS typification were proposed. A problem that were resulted from pattern classification based on binary logic could be solved out by the fuzzy clustering and classification nodes could be reduced by using the proposed new feature vector. The accurate representative beat could be obtained by excluding the ST-T segment that happened outlier through ST-T segment typification procedure.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권4호
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• pp.270-275
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• 2008

Under ubiquitous environment, recommendation system is using the collaborative filtering methods by quantifying context information, but insufficient context information can cause inaccurate recommendation result. In order to solve such problems, the researcher used context information and user's profile. But service history information in users' profiles can have the problems of being influenced by change of the user's taste or fashion as time passes by. In addition, context information and user's profile can't be properly inter-locked according to situation, which can cause inaccurate predictability. In this paper, in case a user's taste or fashion is changed as time passes by, the researcher didn't apply bundled-up value to the user's profile but applied different weight according to change of time. And the researcher could solve the problem that context information and a user's profile can't be properly inter-locked according to situation by applying different weight to the result gained by means of collaborative filtering and then by unifying it. In such ways, the researcher could improve predictability.