• 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.

• 제어로봇시스템학회논문지
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• 제7권7호
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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.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권3호
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• pp.187-192
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• 2012

This paper is concerned with stabilization problem of continuous-time Takagi-Sugeno fuzzy systems. To do this, the stabilization problem is investigated based on the new fuzzy Lyapunov functions (NFLFs). The NFLFs depend on not only the fuzzy weighting functions but also their first-time derivatives. The stabilization conditions are derived in terms of linear matrix inequalities (LMIs) which can be solved easily by the Matlab LMI Toolbox. Simulation examples are given to illustrate the effectiveness of this method.

• 한국지능시스템학회논문지
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• 제8권5호
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• pp.51-60
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• 1998

퍼지 시스템의 안정도와 퍼지 제어기의 설계 방법론에 관한 연구는 최근 들어 많은 주목을 받아왔다. 본 논문은 TS(Takagi-Sugeno) 퍼지 모델로 표현된 비선형 시스템에 대한 제어기 설계분제가 선형행렬부등식(LMI, linear matrix inequality)을 포함하는 convex 문제로 간략화됨을 보인다. 입력행렬의 구조에 따라서 TS 퍼지 시스템을 세 가지로 분류하고, 각각에 대해 선형행렬부등식을 이용한 제어기 설계 방법을 제시한다. 또한 안정도 이외의 성능용건을 고려한 제어기를 설계한다. 제안된 설계 방법론을 설명하기 위해 예제를 다룬다.

• 한국지능시스템학회논문지
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• 제12권5호
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• pp.481-486
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• 2002

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-5) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control. Based on the derived design method, the parameter estimation for controllable canonical T-S fuzzy model is also Presented.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권4호
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• pp.277-283
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• 2013

In this study, we propose a novel method for modeling dynamic hysteresis. Hysteresis is a widespread phenomenon that is observed in many physical systems. Many different models have been developed for representing a hysteretic system. Among them, the Duhem model is a classical nonlinear dynamic hysteresis model satisfying the properties of hysteresis. The purpose of this work is to develop a novel method that expresses the local dynamics of the Duhem model by a linear system model. Our approach utilizes a certain type of fuzzy system that is based on Takagi-Sugeno (T-S) fuzzy models. The proposed T-S fuzzy Duhem model is achieved by fuzzy blending of the linear system model. A simulated example applied to shape memory alloy actuators, which have typical hysteretic properties, illustrates the applicability of our proposed scheme.

• 한국지능시스템학회논문지
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• 제17권1호
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• pp.130-135
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• 2007

In this paper, a direct model reference adaptive fuzzy control (MRAFC) scheme is developed for the plant model whose structure is represented by the MIMO Takagi-Sugeno fuzzy model. The MRAFC scheme is proposed to provide asymptotic tracking of a reference signal lot the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee that all signals in the closed-loop system are bounded. In addition, the plant state tracks the state of the reference model asymptotically with time tot any bounded reference input signal.

• International Journal of Control, Automation, and Systems
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• 제2권1호
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• pp.68-75
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• 2004

In this paper, an estimator with an appropriate adaptive law for updating parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the parameterized plant model. Using the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for indirect adaptive fuzzy control.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
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• pp.80-83
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• 2003

In this note, a separation principle of the Takagi-Sugeno (T-S) fuzzy-model-based controller/observer is investigated. The separation principle of T-S fuzzy-model-based controller/observer sharing the premise parts in the fuzzy rule with directly measurable premise variables is well established. In that case, the fact that the augmented observer-based control system has the eigenvalues of the sub-closed-loop control system by the state-feedback controller and the sub-closed-loop observer error system is used to prove the separation principle. This paper studies the separation principle of T-S fuzzy-model-based controller/observer in which the premise variables cannot be directly measurable.