• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2723-2725
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• 2005

In this paper, a robust $H{\infty}$ stabilization problem to a uncertain discrete-time nonlinear systems with time-delay via fuzzy static output feedback is investigated. The Takagi-Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear systems with time-delayed state. Then parallel distributed compensation technique is used for designing of the robust fuzzy controller. Using a single Lyapunov function, the globally asymptotic stability and disturbance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust $H{\infty}$ controllers are given in terms of linear matrix inequalities via similarity transform and congruence transform technique.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1486-1491
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• 2005

In this paper, a robust H${\infty}$ stabilization problem to a uncertain fuzzy systems with time-varying delay via static output feedback is investigated. The Takagi-Sugeno (T-S) fuzzy model is employed to represent uncertain nonlinear systems with time-varying delayed state, which is a continuous-time or discrete-time system. Using a single Lyapunov function, the globally asymptotic stability and disturbance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust H${\infty}$controllers are given in terms of linear matrix inequalities.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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• pp.121-124
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• 2006

본 논문에서는 Bacterial Foraging Algorithm과 FCM(fuzzy c-means)클러스터링을 이용하여 TSK(Takagi-Sugeno-Kang)형태의 퍼지 규칙 생성과 퍼지 시스템(FCM-ANFIS)을 효과적으로 구축하는 방법을 제안한다. 구조동정에서는 먼저 PCA(Principal Component Analysis)을 이용하여 입력 데이터 성분간의 상관관계를 제거한 후에 FCM을 이용하여 클러스터를 생성하고 성능지표에 근거해서 타당한 클러스터의 수, 즉 퍼지 규칙의 수를 얻는다. 파라미터 동정에서는 Bacterial Foraging Algorithm을 이용하여 전제부 파라미터를 최적화 시킨다. 결론부 파라미터는 RLSE(Recursive Least Square Estimate)에 의해 추정되어진다. PCA(Principal Component Analysis)와 FCM을 적용함으로써 타당한 규칙 수를 생성하였고 Bacterial Foraging Algorithm을 이용하여 최적의 전제부 파라미터를 구하였다. 제안된 방법의 성능을 평가하기 위하여 Box-Jenkins의 가스로 데이터와 Rice taste 데이터의 모델링에 적용하였고 우수한 성능을 보임을 알 수 있었다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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• pp.159-163
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• 2006

본 논문에서는 비선형 시스템의 슬라이딩 모드 관측기 설계에 대해서 논의한다. 제어 대상인 비선형 시스템을 모델링 하는데 있어서 Takagi-Sugeno(T-S) 퍼지 모델 기법을 이용하였고, 이 때 발생할 수 있는 모델 불확실성과 외란에 대해 그것의 최대 최소 범위를 안다고 가정하였다. 제안된 시스템의 LMI (Linear Matrix Inequality)를 기반으로 한 슬라이딩 모드 관측기 설계 방법에서는 관측기와 시스템의 차이를 슬라이딩 표면으로 설정한다. 안정한 슬라이딩 표면을 갖는 슬라이딩 관측기의 존재 가능성을 선형 행렬 부등식의 형태로 표현한다. 슬라이딩 모드 관측기 이득은 LMI 존재 조건의 해를 이용하여 구한다.

• 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.

• Transactions on Control, Automation and Systems Engineering
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• 제2권4호
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• pp.248-254
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• 2000

This paper presents and output feedback fuzzy H(sup)$\infty$ control problem for a class of nonlinear systems with time-varying delayed state. The Takagi-Sugeno fuzzy model is employed to represent a nonlinear systems with time-varying delayed state. Using a single quadratic Lyapunov function, the globally exponential stability and disturance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of fuzzy H(sup)$\infty$ controllers are given in terms of matrix inequalities. Constructive algorithm for design of fuzzy H(sup)$\infty$ controller is also developed. A simulation example is given to illustrate the performance of the proposed design method.

• 제어로봇시스템학회논문지
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• 제18권1호
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• pp.1-6
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• 2012

In this paper, an adaptive fuzzy control system is proposed for the speed control of the ASV (Autonomous Surface Vehicle) with nonaffine nonlinear system dynamics. We consider the turning speed of the screw propeller to be the control input instead of thrust so that we do not have to know the exact function between turning speed and thrust. But in this case, the ASV becomes a nonaffine nonlinear system because thrust is a nonlinear function of the turning speed. To solve this problem, we propose a Takagi-Sugeno fuzzy-model-based control system and simulation studies are performed. Simulation results show the effectiveness of the proposed control scheme.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.231-236
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• 2002

In this paper, we present an analysis and design method fur the control of input-saturated nonlinear systems with the time-delay. The target system is represented by Takagi-Sugeno (T-S) fuzzy model and the parallel distributed compensation (PDC) controller is designed to guarantee the local stability of the equilibrium point. We derive the sufficient condition for the local stability by applying Lyapunov-krasovskii theorem and this condition is converted into the LMI problem.

• 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.

• 한국정밀공학회지
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• 제16권6호
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• pp.166-175
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• 1999

This paper describes a design and performance evaluation of robust controller which overrides unstable motion and pulls out quickly after water entry of underwater vehicle dropped from aircraft or surface ship. We use 6-DOF equation for model of motions and assume parameter uncertainty to reflect the difference of real motion from modelled motion equation. we represent a nonlinear system with uncertainty as Takagi and Sugeno's(T-S) fuzzy models and design controller stabilizing them. The fuzzy controller utilizes the concept of so-called parallel distributed compensation (PDC). Finally, we confirm stability and performance of the controller through computer simulation and hardware in the loop simulation (HILS).