• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.310-316
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• 1998

본 논문에서는 기존의 퍼지 제어규칙에비해 좋은 성능을 갖는 T-S(Takagi-Sugeno)퍼지 모델을 자기조직화 지도와 역전파 신경망을 이용하여 표현하고 제어기 구현을 위한 규칙의 자동 생성 방법을 제안한다. 제안된 방법은 신경망에 기초하여 T-S 퍼지 제어 규칙을 포현하므로써 학습 기능을 이용하여 지식 획득을 용이하게 하고, 입력 변수간의 퍼지 관계에 기반 하여 추론이 이루어지므로 각 퍼지 변수에 대한 소속 함수의 정의 과정이 불필요하게 된다. 또한 제어기로 구현되었을 때 규칙의 수나 퍼지화 및 비퍼지화 등이 구성된 추론망을 통하여 자동으로 수행될 수 있다. 때문에 퍼지 시스템의 구현이 쉽게 이루어 질 수 있게 한다. 제안된 방법을 자동차 궤도 안정화 모의 실험에 적용해 봄으로써 추론망이 규칙을 생성하여 타당한 추론을 하게 됨을 확인한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1230-1233
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• 1993

Numerical solution of inverse problem of Takagi-Sugeno fuzzy model is proposed. The method is located on the application of numerical optimization to the fuzzy model. Steepest descent method is used for the numerical optimization. We use the linear approximation of fuzzy model, called pseudo first order approximation, by fixing the membership value on the neighborhood of the corresponding input. It is introduced in order to reduce the difficulty of optimization process. The efficiency of this method is shown by a numerical experiment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.84-87
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• 2002

This paper presents an adaptive PID control scheme with fuzzy model for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model was used to estimate the error of control input, and the parameter of PID controller was adapted from the error The parameter of TSK fuzzy model was also adapted to plant by comparing the activity output of plant and model output. PID controller which was adapted the uncertainty of nonlinear plant and the change of parameter can be designed by using the presented method. The usefullness of algorithm which was proposed by the simulation of several nonlinear system was also certificated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.126-129
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• 2002

An intelligent digital redesign technique (IDR) for the observer-based output feedback Takagi-Sugeno (T-5) fuzzy control system with fuzzy outputs is developed. The considered IDR condition is cubically parameterized as convex minimization problems of the norm distances between linear operators to be matched.'rho stability condition is easily embedded and the separations principle is explicitly shown.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.1
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• pp.45-51
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• 2001

본 논문은 이산 시간 Takagi-Sugeno (TS) 퍼지 시스템에 대한 출력 추종 제어기 설계에 관하여 연구한다. 출력 추종 제어기의 설계를 위하여 이산 시간 TS 퍼지 시스템을 불확실성을 포함한 선형 시스템의 집합으로서 표현하는 기법을 제시한다. 시스템의 상태에 대하여 어파인 변환을 하여 출력 추종 제어문제를 안정화 문제로 변환한다. 점근적 추종성능을 보장하는 제어기 설계를 위한 충분조건은 선형 행렬 부등식의 형태로 표현되면 주어진 제어기 설계의 해는 여러 가지 수치적 기법을 이용하여 효율적으로 구해질 수 있다. 트레일러 트럭의 임의의 위치에 후진 주차시키기 위한 제어기 설계의 예를 통하여 본 논문에서 제안한 추종 제어 기법의 효용성을 검증한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.309-314
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• 2009

This paper presents implementation of the adaptive neuro-fuzzy control method. Control performance of the adaptive neuro-fuzzy control method for a popular inverted pendulum system is evaluated. The inverted pendulum system is designed and built as an education kit for educational purpose for engineering students. The educational kit is specially used for intelligent control education. Control purpose is to satisfy balancing angle and desired trajectory tracking performance. The adaptive neuro-fuzzy controller has the Takagi-Sugeno(T-S) fuzzy structure. Back-propagation algorithm is used for updating weights in the fuzzy control. Control performances of the inverted pendulum system by PID control method and the adaptive neuro-fuzzy control method are compared. Control hardware of a DSP 2812 board is used to achieve the real-time control performance. Experimental studies are conducted to show successful control performances of the inverted pendulum system by the adaptive neuro-fuzzy control method.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2117-2119
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• 2001

This paper proposes a novel intelligent digital redesign technique for a class of nonlinear systems represented by input-delayed Takagi-Sugeno (TS) fuzzy systems. The digitally redesigned controller can show good performance provided that the analog controller is well-designed. The developed digital redesign technique is based on the 'state-matching', so the control performance is guaranteed as well as the stability of the system. An simulation example is included to ensure the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2005-2007
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• 2001

A controller design problem for a discrete-time Takagi-Sugeno (TS) fuzzy systems is discussed. The switching-type controller is employed in this study. A switching-type fuzzy-model-based controller is constructed based on the spirit of "devide and conquer". The design condition of this controller is formulated in terms of linear matrix inequalities (LMIs), which guarantees the global stability of the controlled TS fuzzy systems. An example is included for ensuring the effecienct of the proposed control method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.11
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• pp.2119-2130
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• 2011

This paper proposes new delay-dependent robust stability criteria for neural networks with time-varying delays. By construction of a suitable Lyapunov-Krasovskii's (L-K) functional and use of Finsler's lemma, new stability criteria for the networks are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Two numerical examples are given to illustrate the effectiveness of the proposed methods.