• 전자공학회논문지B
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• 제33B권12호
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• pp.84-94
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• 1996

In this work, a fuzzy petri net model for modeling a general form of fuzzy production system which consists of chaining fuzzy production rules and so requires multistage reasoning process is presented. For the obtained fuzzy petri net model, the net will be transformed into some matrices, and also be systematically led to an algebraic form of a state equation. Since it is fond that the approximate reasoning process in fuzzy systems corresponds to the dynamic behavior of the fuzzy petri net, it is further shown that the multistage reasoning process can be carried out by executing the state equation.

• 한국지능시스템학회논문지
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• 제18권6호
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• pp.762-767
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• 2008

본 논문에서는 TS 퍼지 모델로 표현되는 시간 지연 비선형 시스템에 대한 $L_{\infty}$ 이득 상태 제한 퍼지 제어기를 제안한다. 이 위해 먼저 TS 퍼지 모델을 이용하여 시간 지연 비선형 시스템을 모델링한다. 다음 이 퍼지 모델을 기본으로 $L_{\infty}$ 이득을 얻기위해 퍼지 상태 궤환 제어기를 설계한다. 마지막으로 $L_{\infty}$ 이득을 얻기 위한 충분조건을 유도한다. 충분조건은 선형 행렬 부등식의 형태로 공식화 한다. 마지막으로 몇 가지 예제를 통하여 제안된 제어기의 효율성을 증명한다.

• 전자공학회논문지CI
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• 제38권4호
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• pp.1-9
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• 2001

본 논문에서는 한 개의 서버와 시스템용량 K를 갖는 M/M/1/K 큐잉네트워크모델에 펴지집합이론을 적용한 퍼지 M/M/1/K 큐잉네트워크모델을 제안하였다. 작업의 도착율과 서버의 서비스율의 형태가 언어적 속성으로 표현될 때， 이 모델을 사용하여 시스템의 해석이 가능해진다. 시스템의 평가를 위해서 시스템내 평균작업수， 작업 평균진입률， 그리고 작업 평균소요시간 등 시스템의 주요 평가측도를 유도하였다. 퍼지 작업 환경에서 이러한 결과식들의 유효함을 검증하기 위하여， 제안된 모델에 다양한 퍼지도착율 ${\lambda}$와 퍼지서비스율 ${\mu}$에 대하여 시스템용량 K 값의 변화에 따른 성능평가를 컴퓨터 시뮬레이션하였다. 그 결과가 제안한 퍼지 모델에서 예측한 평가와 일치함을 확인하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권3호
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• pp.184-189
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• 2006

This paper deals with a fractional model reduction for T-S fuzzy systems with time varying delayed states. A contractive coprime factorization of time delayed T-S fuzzy systems is defined and obtained by solving linear matrix inequalities. Using generalized controllability and observability gramians of the contractive coprime factor, a balanced state space realization of the system is derived. The reduced model will be obtained by truncating states in the balanced realization and an upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is performed.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.225-231
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• 1998

TSK fuzzy system can represent effectively the behavior of a complex nonlinear system with low number of rules with the desired accuracy and guarantee the stability of the closed loop system, while the interpretation of the rules is difficult due to the functional nature of the consequents. On the contrary, fuzzy controller with singleton consequents is understandable intuitively and adjustable the rules easily due to qualitative expression of the rules. Ideally, one would like to combine the positive identification properties of TSK fuzzy system with the advantages of fuzzy controller with singleton consequents. Therefore, this paper suggests a method transforming TSK fuzzy systems into fuzzy systems with singleton consequents, and shows its application designing a fuzzy controller with singleton consequents by using the TSK fuzzy system when the behavior of a nonlinear system is described with a singleton fuzzy model by human esper.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.528-530
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• 1999

This paper addresses the analysis and design of fuzzy control systems for a class of complex single input single output nonlinear systems. Firstly, the nonlinear system is represented by well-known Takagai-Sugeno (TS) fuzzy model and the global controller is constructed by compensating each linear model in the rule of TS fuzzy model. The design of conventional TS fuzzy-model-based controller usually is composed of two processes. One is to determine static state feedback gain of each local model and the other is to validate the stability of the designed fuzzy controller. In this paper, we propose an alternative of the design of TS fuzzy-model-based controller. The design scheme is based on the extension of conventional optimal control theory to the design of TS fuzzy-model-based controller. By using the proposed method the design and stability analysis of the TS fuzzy model-based controller is reduced to the problem of finding the solution of a set of algebraic Riccati equations. And we use the recently developed interior point method to find the solution of AREs, where AREs are recast as the LMI formulation. One simulation example is given to show the effectiveness and feasibility of the proposed fuzzy controller design method.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권2호
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• pp.107-113
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• 2004

This paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of permanent magnet synchronous motor(PMSM) drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed adaptive fuzzy controller is confirmed by performance results for PMSM drive system.

• Journal of Electrical Engineering and Technology
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• 제3권1호
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• pp.101-107
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• 2008

We introduce an optimization of fuzzy set-fuzzy systems based on IG (Information Granules). The proposed fuzzy model implements system structure and parameter identification by means of IG and GAs. The concept of information granulation was coped with to enhance the abilities of structural optimization of the fuzzy model. Granulation of information realized with C-Means clustering helps determine the initial parameters of the fuzzy model such as the initial apexes of the membership functions in the premise part and the initial values of polynomial functions in the consequence part of the fuzzy rules. The initial parameters are adjusted effectively with the help of the GAs and the standard least square method. To optimally identify the structure and the parameters of the fuzzy model we exploit GAs with successive tuning method to simultaneously search the structure and the parameters within one individual. We also consider the variant generation-based evolution to adjust the rate of identification of the structure and the parameters in successive tuning method. The proposed model is evaluated with the performance of the conventional fuzzy model.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.122-125
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• 2002

This paper proposes a stability condition in switched system and then, introduce design method of fuzzy-model-based controller which guarantees the stability. Takagi-Sugeno(75) fuzzy model is employed to design a switching-type fuzzy-model-based ,controller. Furthermore, it is proposed that the design method stabilizing continuous and discrete-time 75 fuzzy model respectively. Each controller in each subspace stabilize the subsystem respectively. In order to guarantee the stability of the global system, it is required to guarantee the stability condition in boundaries with subsystems. The condition which guarantees the stability in boundaries is presented in this paper. Inverted Pendulum system is employed to execute computer simulations. In this computer simulation, the performance of the proposed controller is verified by the control result.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권2호
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• pp.139-145
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• 2002

In this paper, we proposed an intelligent digital redesign method for a class of fuzzy-model-based controllers, effective fur stabilization of continuous-time nonlinear systems. The TS fuzzy model is used to expend the results of the digital redesign technique to nonlinear systems. The proposed method utilized the recently developed LMI technique to obtain a digitally redesigned fuzzy-model-based controller. The intelligent digital redesign problem is converted to equivalent problem, and the LMI method is used to find the digitally redesigned fuzzy-model-based controller. The stabilization conditions of TS fuzzy model are derived for stabilization in the sense of Laypunov stability. In order to demonstrates the effectiveness and feasibility of the proposed controller design methodology, we applied this method to the single link flexible-joint robot arm.