• Journal of the Korean Society for Library and Information Science
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• v.21
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• pp.249-290
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• 1991

Theoretical developments in the information retrieval have offered a number of alternatives to traditional Boolean retrieval. Probability theory and fuzzy set theory have played prominent roles here. Fuzzy set theory is an attempt to generalize traditional set theory by permitting partial membership in a set and this means recognizing different degrees to which a document can match a request. In this study, an experimentation of a document retrieval system using the fuzzy relation matrix of the keywords is described and the results are offered. The queries composed of keywords and Boolean operaters AND, OR, NOT were processed in the retrieval method, and the method was implemented on the PC of 32bit level (30 MHz) in an experimental system. The measurement of the recall ratio and precision ratio verified the effectiveness of the proposed fuzzy relation matrix of keywords and retrieval method. Compared to traditional crisp method in the same document database, the recall ratio increased $10\%$ high although the precision ratio decreased slightly. The problems, in this experiment, to be resolved are first, the design of the automatic data input and fuzzy indexing modules, through which the system . can have the ability of competition and usefulness. Second, devising a systematic procedure for assigning fuzzy weights to keywords in documents and in queries.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.549-554
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• 2012

In this paper, we consider the optimal fuzzy filter of nonlinear discrete-time with estimation error variance constraint. First, the Takagi and Sugeno(T-S) fuzzy model is employed to approximate the nonlinear system. Next, the error state is mean square bounded, and the steady state variance of the estimation error of each state is not more than the individual predefined value. It is shown that, the addressed problem can be carried out by solving linear matrix inequality(LMI) and some algebraic quadratic matrix inequalities. Finally, some examples are provided to illustrate the design procedure and expected performance through simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.302-306
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• 2011

This paper presents Takagi-Sugeno (T-S) fuzzy-model-based controller for depth control of autonomous underwater vehicles(AUVs). Through sector nonlinearity methodology, The nonlinear AUV is represented by T-S fuzzy model. By using the Lyapunov function, the design condition of controller is derived to guarantee the performance of depth control in the format of linear matrix inequality (LMI). An example is provided to illustrate the effectiveness of the proposed methodology.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.220-222
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• 2006

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated lineal operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a T-S fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.506-515
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• 2006

This paper studies an intelligent digital control for nonlinear systems with multirate sampling. It is worth noting that the multirate control design is addressed for a given nonlinear system represented by Takagi-Sugeno (T-S) fuzzy models. The main features of the proposed method are that i) it is provided that the sufficient conditions for stabilization of the discrete-time T-S fuzzy system in the sense of Lyapunov stability criterion, which is can be formulated in the linear matrix inequalities (LMIs); and ii) the stability properties of the trivial solution of the digital control system can be deduced from that of the solution of its discretized versions. An example is provided for showing the feasibility of the proposed method.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2516-2518
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• 2004

This paper proposes a stability condition in discrete-time affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties and then, introduces the design method of a fuzzy-model-based controller which guarantees the stability. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of linear matrix inequalities (LMIs).

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.44-49
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• 1999

This paper presents a new T-S(Tae-Sugeno) fuzzy controller design method satisfying the output energy bound. Maximum output energy via a quadratic Lyapunov function to obtain the bound on output energy is derived. LMI(Linear Matrix Inequality) problems which satisfy an output energy bound for both of the continuous-time and discrete-time T-S fuzzy control system are also derived. Solving these LMIs simultaneously, we find a common symmetric positive definite matrix P which guarantees the global asymptotic stability of the system and stable feedback gains K's satisfying the output energy bound. A simple example demonstrates validity of the proposed design method.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.239-246
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• 2010

This paper proposes a new document clustering method using NMF and fuzzy relationship. The proposed method can improve the quality of document clustering because the clustered documents by using fuzzy relation values between semantic features and terms to distinguish well dissimilar documents in clusters, the selected cluster label terms by using semantic features with NMF, which is used in document clustering, can represent an inherent structure of document set better. The experimental results demonstrate that the proposed method achieves better performance than other document clustering methods.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.589-596
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• 2001

In this paper, a new design methodology for the optimal control of nonlinear systems described by the TS(Takagi-Sugeno) fuzzy model is proposed. First, a new theorem concerning the optimal stabilizing control of a general nonlinear dynamic system is proposed. Next, based on the proposed theorem and the inverse optimal approach, an optimal controller synthesis procedure for a TS fuzzy system is given, Also, it is shown that the optimal controller can be found by solving a linear matrix inequality problem. Finally, the proposed method is applied to the attitude control of a rigid spacecraft to demonstrate its validity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2037-2045
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• 2016

This paper presents a fuzzy-model-based design approach to the buoyancy and moment controls of a class of nonlinear underwater glider. Through the linearization and the sector nonlinearity methodologies, the underwater glider dynamics is represented by a Takagi-Sugeno (T-S) fuzzy model. Sufficient conditions are derived to guarantee the asymptotic stability of the closed-loop system in the format of linear matrix inequality (LMI). Simulation results demonstrate the effectiveness of the proposed buoyancy and moment controllers for the underwater glider.