• Structural Engineering and Mechanics
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• 제22권4호
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• pp.469-481
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• 2006

A new method called fuzzy factor method for the stationary stochastic response analysis of fuzzy truss with global fuzzy structural parameters is presented in this paper. Considering the fuzziness of the structural physical parameters and geometric dimensions simultaneously, the fuzzy correlation function matrix of structural displacement response in time domain is derived by using the fuzzy factor method and the optimization method, the fuzzy mean square values of the structural displacement and stress response in the frequency domain are then developed with the fuzzy factor method. The influences of the fuzziness of structural parameters on the fuzziness of mean square values of the displacement and stress response are inspected via an example and some important conclusions are obtained. Finally, the example is simulated by Monte-Carlo method and the results of the two methods are close, which verified the feasibility of the method given in this paper.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.358-363
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• 1998

An algorithm for representing the cubic spline interpolation of differentiable functions by a fuzzy system is presented in this paper. The cubic B-spline functions which form a basis for the interpolation function are used as the fuzzy sets for input fuzzification. The ordinal number of the coefficient cKL in the list of the coefficient cij's as sorted in increasing order, is taken to be the output fuzzy set number in the (k, l) th entry of the fuzzy rule table. Spike functions are used for the output fuzzy sets, with cij's as support boundaries after they are sorted. An algorithm to compute the support boundaries explicitly without solving the matrix equation involved is included, along with a few properties of the fuzzy rule matrix for the designed fuzzy system.

• 한국정밀공학회지
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• 제12권12호
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• pp.139-148
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• 1995

In this paper an electro-hydraulic servo system is designed by using a fuzzy control algorithm. In order to drive an optimal fuzzy control system, a simulation program for the control system has been developed. By this program the fuzzifier and defuzzifier, a fuzzy inference method, a fuzzy relational matrix, and a fuzzy inference method are investigated. As a result, Larsen inference method, 9*9 fuzzy relational matrix, and center of area defuzzifier are turned out the best as parameters. Finally this method is compared with the conventional PID algotithm, and showed that the fuzzy control performs better than PID algorithm. The fuzzy control performs very well adap- tation against uncertain disturbances.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.326-330
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• 1998

There have been several recent studies concerning the stability of fuzzy control systems and the synthesis of stabilizing fuzzy controller. This paper reports on a related study of the TS(Takagi-Sugeno) fuzzy systems, and it is shown that the controller synthesis problems for the nonlinear systems described by the TS fuzzy model can be reduced to convex problems involving LMIs(Linear matrix inequalities). After classifying the TS fuzzy systems into two families based on how diverse their input matrices are, different controller synthesis procedure is given for each of these families. A numerical example is presented to illustrate the synthesis procedures developed in this paper.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.133-136
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• 2004

This paper proposes a stability condition in 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).

• International Journal of Control, Automation, and Systems
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• 제5권3호
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• pp.349-354
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• 2007

This paper considers the problem of designing static output feedback controllers for nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models. Based on linear matrix inequality technique, a new method is developed for designing fuzzy stabilizing controllers via static output feedback. Furthermore, the result is also extended to $H_{\infty}$ control. Examples are given to illustrate the effectiveness of the proposed methods.

• 논리연구
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• 제10권2호
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• pp.125-146
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• 2007

This paper investigates the relevance system R-mingle (RM) as a a fuzzy-relevance logic. It shows that RM is fuzzy in Cintula's sense, i.e., RM is complete with respect to linearly ordered L-matrices (or L-algebras). More exactly, we first introduce RM and its weak versions wwRM and wRM. We next provide algebraic and matrix completeness results for them.

• 한국지능시스템학회논문지
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• 제10권5호
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• pp.423-431
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• 2000

In this paper, the effect of computing time-delay in the real-time digital fuzzy control systems is investigated and the design methodology of a real-time digital fuzzy controller(DFC) to overcome the problems caused by it is presented. We propose the fuzzy feedback controller whose output is delayed with unit sampling period. The analysis and the design problem considering computing time-delay is very easy because the proposed controller is syncronized with the sampling time. The stabilization problem of the digital fuzzy control system is solved by the linear matrix inequality(LMI) theory. Convex optimization techniques are utilized to find the stable feedback gains and a common positive definite matrix P for the designed fuzzy control system Furthermore, we develop a real-time fuzzy control system for backing up a computer-simulated truck-trailer with the consideration of the computing time-delay. By using the proposed method, we design a DFC which guarantees the stability of the real time digital fuzzy control system in the presence of computing time-delay.

• Transactions on Control, Automation and Systems Engineering
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• 제4권4호
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• pp.356-362
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• 2002

In this paper, well-known Takagi-Sugeno fuzzy model is used as the nonlinear plant model and uncertainty is assumed to be included in the model structure with known bounds. Based on the fuzzy models, a numerical robust stability analysis for the fuzzy feedback linearization regulator is presented using Linear Matrix Inequalities (LMI) Theory. For these structured uncertainty, the closed system can be cast into Lur'e system by simple transformation. From the LMI stability condition for Lur'e system, we can derive the robust stability condition for the fuzzy feedback linearization regulator based on Takagi-Sugeno fuzzy model. The effectiveness of the proposed analysis is illustrated by a simple example.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권2호
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• pp.187-193
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• 2003

In this paper, a systematic design method of the intelligent PAM fuzzy controller for nonlinear systems using the efficient tools-Linear Matrix Inequality and the intelligent digital redesign is proposed. In order to digitally control the nonlinear systems, the TS fuzzy model is used for fuzzy modeling of the given nonlinear system. The convex representation technique also can be utilized for obtaining TS fuzzy models. First, the analog fuzzy-model-based controller is designed such that the closed-loop system is globally asymptotically stable in the sense of Lyapunov stability criterion. The simulation results strongly convince us that the proposed method has great potential in the application to the industry.