• 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.

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.506-515
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• 2006

This paper studies an intelligent digital control for nonlinear systems with multirate sampling. It is worth noting that the multirate control design is addressed for a given nonlinear system represented by Takagi-Sugeno (T-S) fuzzy models. The main features of the proposed method are that i) it is provided that the sufficient conditions for stabilization of the discrete-time T-S fuzzy system in the sense of Lyapunov stability criterion, which is can be formulated in the linear matrix inequalities (LMIs); and ii) the stability properties of the trivial solution of the digital control system can be deduced from that of the solution of its discretized versions. An example is provided for showing the feasibility of the proposed method.

• 한국지능시스템학회논문지
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• 제15권2호
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• pp.185-190
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• 2005

본 논문은 파리미터의 불확실성을 포함하는 Takagi-Sugeno(T-S) 퍼지 시스템을 위한 체계적인 출력 추종 제어기 설계기법을 제안한다. 불확실 T-S 퍼지 시스템은 효과적인 설계를 위하여 퍼지 입력 공간의 발화도의 우세성에 따르는 몇 개의 불확실 선형 시스템으로 표현된다. 출력 추종 제어 오차는 일반화된 리아푸노프 함수에 의하여 해석된다. 이에 따라 출력 추종 제어기 설계 문제는 몇 개의 불확실 선형 시스템의 안정화 문제로 변환된다. 강인 추종 제어기 설계 조건은 선형행렬 부등식의 형태로 유도된다. 마지막으로 파라미터 불확실성을 포함하는 혼돈 로렌Cm 카오스 시스템의 출력 추종 문제를 고려하여 본 논문에서 제안한 기법의 효용성을 입증한다.

• 한국지능시스템학회논문지
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• 제23권2호
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• pp.133-138
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• 2013

본 논문은 연속시간에서의 타카키-수게노 퍼지모델 기반 다개체 시스템의 상태일치를 위한 제어기 설계 기법을 제안한다. 그래프 이론을 통해 각 개체간의 정보를 교환하는 네트워크를 표현한다. 제어기 설계 조건은 선형 행렬 부등식의 형태로 유도되며, 수치적 예제를 통해 제안된 방법의 효율성을 증명한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.658-662
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• 2004

This paper develops a stability analysis and controller synthesis methodology for a continuous-time affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties. Affine T-S fuzzy system can be an advantage because it may be able to approximate nonlinear functions to high accuracy with fewer rules than the homogeneous T-S fuzzy systems with linear consequents only. 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 bilinear matrix inequalities (BMIs). A simulation example is given to illustrate the application of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권1호
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• pp.52-57
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• 2006

In this paper, we have proposed a new adaptive fuzzy control algorithm based on Takagi-Sugeno fuzzy model. The regulation problem for the uncertain SISO nonlinear system is solved by the proposed algorithm. Using the advanced stability theory, the stability of the state, the control gain and the parameter approximation error is proved. Unlike the existing feedback linearization based methods, the proposed algorithm can guarantee the global stability in the presence of the singularity in the inverse dynamics of the plant. The performance of the proposed algorithm is demonstrated through the problem of balancing and swing-up of an inverted pendulum on a cart.

• 한국지능시스템학회논문지
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• 제12권6호
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• pp.554-558
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• 2002

In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

• 조명전기설비학회논문지
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• 제16권6호
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• pp.80-86
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• 2002

본 논문에서는 쌍선형 시스템으로 표현되는 화력발전소 과열기에 대한 퍼지 제어기법을 제안한다. 증기온도를 제어하기 위하여 쌍선형 관측기로부터 얻어진 추정값과 기준값의 오차면적과 시간 변화율을 고려하여 입력변수를 구성하고, T. Takagi와 M. Sugeno의 퍼지모델을 기반으로 제어규칙을 추론하였다. 제안된 방법의 유용성은 컴퓨터 시뮬레이션 결과에 의해서 검증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.169.3-169
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• 2001

This paper introduces a new approach to analysis of error convergence for a class of iterative learning control systems. First, a nonlinear plant is represented using a Takagi-Sugeno(T-S) fuzzy model. Then each iterative learning controller is designed for each linear plant in the T-S fuzzy model. From the view point of two-dimensional(2-D) system theory, we transform the proposed learning systems to a 2-D error equation, which is also established in the form of T-S fuzzy model. We analysis the error convergence in the sense of induced 2 L -norm, where the effects of disturbances and initial conditions on 2-D error are considered. The iterative learning controller design problem to guarantee the error convergence can be reduced to linear matrix inequality problems. In comparison with others, our learning algorithm ...

• 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.