• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2302-2304
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• 2000

This paper addresses a fuzzy controller for nonlinear systems control using a pole placement in a specified disk. In the method, we linearize a nonlinear plant about nominal operating points and represent it using TS fuzzy model and formulate the controller rules. A feedback control law for a local model is determined using a pole placement in a specified disk(${\alpha}$:center ${\gamma}$:radius} region so that the closed loop system is stable. A nonlinear system can be controlled by combining fuzzy controller with a pole placement scheme which can be used to modify the transient response such as damping ratio and overshoot. A stability of overall fuzzy control system is guaranteed in the Lyapunov sense. Finally, it is shown that the proposed method is feasible through a computer simulation.

• 대한전자공학회논문지TE
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• 제39권2호
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• pp.17-28
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• 2002

최근 신경회로망 구조 또는 퍼지논리를 이용한 자력등화 즉, 비선형 등화에 대한 연구가 활발하게 진행되고 있다. 본 논문에서는 계산의 복잡성과 등화 성능 사이에 더 나은 trade-off를 찾기 위해 스텝 크기(step size)를 자동적으로 조절할 수 있는 즉, 에러 오차 값이 크면 계수갱신율을 크게 하고 에러 오차 값이 작으면 계수갱신율을 작게 하여 빠른 수렴비와 낮은 초과 MSE를 갖는 TS(Tagaki-Sugeno) 퍼지 모델과 ISI에 강하고 위상변화에 둔감한 CMA(Constant Modulus Algorithm)를 접목시킨 새로운 FSG (Fuzzy Stochastic Gradient)/CMA 알고리즘을 제안하였다. 제안된 FSG/CMA 알고리즘을 사용한 채널 적응 등화기를 설계하여 모의실험한 결과 기존 알고리즘 보다 3.5dB의 SNR이 개선됨을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.110-112
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• 2000

A new robust digital fuzzy controller design methodology is proposed for load frequency of nonlinear power system with valve position limits of governor in the presence of parametric uncertainties. The Takagi-Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the nonlinear power system. A sufficient condition of robust stability for robust fuzzy control with parametric uncertainties is presented in the sense of Lyapunov. The controller that designed by preposed robust fuzzy controller design method is based compounding condition between continues system and discrete system. The effectiveness of controller that designed by the proposed robust fuzzy controller design method is demonstrated through simulation example.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.496-498
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• 2005

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 linear operators to be matched. Also by using the power series, 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).

• International Journal of Control, Automation, and Systems
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• 제3권2호
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• pp.225-235
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• 2005

This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included in the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.70-70
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• 2000

Recently, a neuro-fuzzy approach, a combination of neural networks and fuzzy reasoning, has been playing an important role in the motor control. In this paper, a novel method of fiction compensation using neuro-fuzzy architecture has been shown to significantly improve the performance of a DC motor system with nonlinear friction characteristics. The structure of the controller is the neuro-fuzzy network with the TS(Takagi-Sugeno) model. A back-propagation neural network based on a gradient descent algorithm is employed, and all of its parameters can be on-line trained. The performance of the proposed controller is compared with both a conventional neuro-controller and a PI controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2314-2316
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• 2000

In the construction of successful fuzzy models and/or controllers for nonlinear systems, identification of a good fuzzy Neural inference system is an important yet difficult problem, which is traditionally accomplished by trial and error process. In this paper, we propose a systematic identification procedure for complex multi-input single- output nonlinear systems with DNA coding method.DNA coding method is optimization algorithm based on biological DNA as are conventional genetic algothms (GAs). We also propose a new coding method for applying the DNA coding method to the identification of fuzzy Neural models. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system.

• Transactions on Control, Automation and Systems Engineering
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• 제1권2호
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• pp.87-93
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• 1999

This paper proposes a systematic designs methodology for the Takagi-Sugeno (TS) model based fuzzy control systems with guaranteed stability and pre-specified transient performance for the application to a nonlinear magnetic bearing system. More significantly, in the proposed methodology , the control design problems which considers both stability and desired transient performance are reduced to the standard LMI problems . Therefore, solving these LMI constraints directly (not trial and error) leads to a fuzzy state-feedback controller such that the resulting fuzzy control system meets above two objectives. Simulation and experimentation results show that the proposed LMI-based design methodology yields only the maximized stability boundary but also the desired transient responses.

• Journal of Mechanical Science and Technology
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• 제17권1호
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• pp.105-113
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• 2003

This paper proposes a systematic design methodology for the Takagi-Sugeno (TS) model based fuzzy state feedback control system with multi-objectives. In this investigation, the objectives are set to be guaranteed stability and pre-specified transient performance, and this scheme is applied to a nonlinear magnetic bearing system. More significantly, in the proposed methodology, the control design problems that consider both stability and desired transient performance are reduced to the standard LMI problems. Therefore, solving these LMI constraints directly (not trial and error) lead to a fuzzy state-feedback controller such that the resulting fuzzy control system meets the above two objectives. Simulation and experimentation results show that the Proposed LMI-based design methodology yields not only maximized stability boundary but also the desired transient responses.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권3호
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• pp.300-305
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• 2004

This paper concerns controller design for the Takagi-Sugeno (TS) fuzzy systems. The design method proposed in this paper is derived in the framework of the optimal control theory utilizing the piecewise quadratic optimal value functions. The major part of the proposed design procedure consists of solving linear matrix inequalities (LMIs). Since LMIs can be solved efficiently within a given tolerance by the recently developed interior point methods, the design procedure of this paper is useful in practice. A design example is given to illustrate the applicability of the proposed method.