• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.165-170
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• 2000

In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, in the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult, SOFC is proposed for a hierachical control structure consisting of basic level and high level that modify control rules.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.80-87
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• 1998

This paper presents and online scheme for fuzzy modelling of nonlinear systems, based on the model adjustment technique and the genetic algorithm technique. The fuzzy model is characterized by fuzzy "if-then" rules which represent locally linear input-output relations whose consequence parts are defined as subsystems of a nonlinear sysem. The discrete-time model for each subsystem is obtained to deal with initalization and unmeasurable signal problems in online estimation and the final output of the fuzzy model is computed from the outputs of the discrete-time models. Then, the parameters of both the premise and consequence parts of the fuzzy model are adjusted by a genetic algorithm. A set of simulation works is carried out to demonstrate the effectiveness of the proposed method.ed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.161-165
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• 2009

Increase of multimedia information in Web requires a new method to manage and service multimedia documents efficiently. This paper proposes a conceptual object grouping method by fuzzy filtering, which is automatically constituted based on increase of multimedia documents. The proposed method composes subsumption relations between conceptual objects automatically using fuzzy filtering of the document objects that are extracted from domains. Grouping of such conceptual objects is regarded as subsumption relation which is decided by $\mu$-cut. This paper proposes $\mu$-cut, FAS(Fuzzy Average Similarity) and DSR(Direct Subsumption Relation) to decide fuzzy filtering, which groups related document objects easily. This paper used about 1,000 conceptual objects in the performance test of the proposed method. The simulation result showed that the proposed method had better retrieval performance than those for OGM(Optimistic Genealogy Method) and BGM(Balanced Genealogy Method).

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.193-198
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• 1999

In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, In the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult, SOFC is proposed for a hierarchical control structure consisting of basic level and high level that modify control rules.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1223-1232
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• 2004

We present a new technique to the design and real-time implementation of fuzzy control system basedon digital signal processors in order to improve the precision and robustness for system of industrial robot in this paper. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C80 is used in implementing real time fuzzy control to provide an enhanced motion control for robot manipulators. In this paper, a Self-Organizing Fuzzy Controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a Fuzzy Logic Controller, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult Self-Organizing Fuzzy Controller is proposed for a hierarchical control structure consisting of basic and high levels that modify control rules. The proposed Self-Organizing Fuzzy Controller scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for a Dual-Arm robot with eight joints.

• Smart Structures and Systems
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• v.20 no.1
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• pp.61-74
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• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.642-647
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• 2004

The relations of fuzzy entropy, distance measure, and similarity measure are discussed in this paper. For the purpose of reliable signal selection, the fuzzy entropy is proposed by a distance measure. Properness of the proposed entropy is verified by the definition of the entropy measure. Fourier and Wavelet transform are applied to the stator current signal to obtain the fault features of an induction motor. Membership functions for 3-phase currents are obtained by the Bootstrap method and Central Limit Theorem. Finally, the proposed entropy is applied to measure the fault signal of an induction machine, and the fuzzy entropy values of phase currents are illustrated.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.97-101
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• 2003

최근 수학구조 및 교수-학습과 관련된 연구에 지식공간 이론을 응용하고자하는 논문들이 많이 나오고 있다. 실제로 유의미 학습과 관련된 수행평가와 수학문제를 푸는 능력에 관한 평가를 연구하는데 지식구조가 응용되고 있지만 이를 활용하는데는 많은 애로사항이 있으며 이를 보완하기 위한 여러 가지 방법이 연구되어오고 있다. 특히, Schrepp교수는 스피드문제의 경우로 제한하여 지식공간론을 응용한 일반화된 수학구조의 연구방법을 제시하였다. 본 논문에서는 주관적 지식의 평가를 하게되는 수학구조 및 공간에 관한 연구를 하는데 효과적으로 응용될 수 있는 퍼지지식공간론에 관한 전반적인 기초 이론을 정의하고 그 성질들을 연구하고자한다.

• Journal of applied mathematics & informatics
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• v.4 no.1
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• pp.147-166
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• 1997

The convergence of the power sequence of an $n{\times}n$ fuzzy matrix has been studied. Some theoretical necessary and sufficient con-ditions have been established for the power sequence to be convergent generally. Furthermore as one of our main concerns the convergence index was studied in detail especially for some special types of Boolean matrices. Also it has been established that the convergence index is bounded by $(n-1)^2+1$ from above for an arbitrary $n{\times}n$ fuzzy matrix if its power sequence converges. Our method is concentrated on the limit behavior of the power se-quence. It helped us to make our proofs be simpler and more direct that those in pure algebraic methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.66-70
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• 2007

Note that Choquet integral is a generalized concept of Lebesgue integral, because two definitions of Choquet integral and Lebesgue integral are equal if a fuzzy measure is a classical measure. In this paper, we consider interval-valued Choquet integrals with respect to fuzzy measures(see [4,5,6,7]). Using these Choquet integrals, we define a mappings on the classes of Choquet integrable functions and give an example of a mapping defined by interval-valued Choquet integrals. And we will investigate some relations between m-convex mappings ${\phi}$ on the class of Choquet integrable functions and m-convex mappings $T_{\phi}$, defined by the class of closed set-valued Choquet integrals with respect to fuzzy measures.