• 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.

• 한국지능시스템학회논문지
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• 제26권4호
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• pp.308-315
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• 2016

본 논문은 이산시간 장주기모델로 구성된 다개체시스템의 타카기-수게노(Takagi-Sugeno: T-S) 퍼지 군집제어 기법을 제안한다. 이산시간 모델은 오일러(Euler) 방법을 이용하여 유도한다. 이에 대한 T-S 퍼지 모델은 피드백 선형화 기법을 통해 구성하며, 이를 점근적으로 안정화하기 위한 퍼지제어기를 설계한다. 제어기 설계조건은 선형행렬부등식의 형태로 표현된다.

• 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.

• 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.

• 제어로봇시스템학회논문지
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• 제20권11호
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• pp.1142-1146
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• 2014

This paper addresses on a $H_{\infty}$ sampled-data stabilization of a Takagi-Sugeno (T-S) fuzzy system. The sampled-data stabilization problem is formulated as a discrete-time stabilization one via a direct discrete-time design approach. It is shown that the sampled-data fuzzy control system is asymptotically stable whenever its exactly discretized model is asymptotically stable. Based on an exact discrete-time model, sufficient design conditions are derived in the format of linear matrix inequalities (LMIs). An example is provided to illustrate the effectiveness of the proposed methodology.

• 제어로봇시스템학회논문지
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• 제8권5호
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• pp.385-392
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• 2002

This paper introduces a new approach to analysis of error convergence for a class of iterative teaming control systems. Firstly, 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 if the form of T-S fuzzy model. We analyze the error convergence in the sense of induced L$_2$-norm, where the effects of disturbances and initial conditions on 2-D error are considered. The iterative teaming controller design problem to guarantee the error convergence can be reduced to the linear matrix inequality problem. This method provides a systematic design procedure for iterative teaming controller. A simulation example is given to illustrate the validity of the proposed method.

• 한국지능시스템학회논문지
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• 제21권3호
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• pp.302-306
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• 2011

본 논문은 무인 잠수정(Autonomous underwater vehicles: AUVs)의 심도 제어를 위한 타카키-수게노 (Takagi-Sugeno: T-S) 퍼지 모델 기반 제어기를 제안한다. Sector nonlinearity 기법을 통해 주어진 비선형 무인 잠수정은 T-S 퍼지 모델로 표현된다. 리아푸노프(Lyapunov) 함수를 이용하여 무인 잠수정의 심도 제어 성능을 보장하는 선형 행렬 부등식(Linear matrix inequality: LMI) 형태의 제어기 설계 조건을 유도한다. 모의 실험을 통해 제안된 기법의 심도 제어 성능을 검증한다.

• 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.

• 융합신호처리학회논문지
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• 제5권4호
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• pp.301-307
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• 2004

본 논문에서는 Takagi-Sugeno(T-S) 퍼지모델에 대한 가변구조제어방식을 제안하며 이를 이용한 바퀴구동 도립 진자의 자세제어를 보인다. 비선형 시스템이 T-S 퍼지모델로 모델링 될 수 있다는 가정 하에서 바퀴구동 도립진자에 대하여 몇 개의 대표 동작점을 기준으로 시스템을 선형화하여 퍼지모델을 얻고 이를 통해 가변구조제어이론을 도입하여 제어기를 설계한다. 제안된 제어법칙은 퍼지모델을 구성하는 각각의 선형 부 시스템의 입력이득 행렬을 동일한 행렬로 단일화하고 그 단일화된 제어이득행렬을 토대로 설계되어진다. 이득행렬의 단일화 과정에서 생성되는 불확실성은 가변구조제어 이론의 입력 외란으로 해석되어질 수 있으며 이러한 단일화 외란은 기존 가변구조제어의 강인성에 의해 해결되어질 수 있다. 바퀴구동 도립진자 시스템 예를 통해 제안된 제어알고리즘의 타당성과 유용성을 보인다.

• 제어로봇시스템학회논문지
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• 제22권7호
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• pp.508-512
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• 2016

This paper discusses a Takagi-Sugeno (T-S) fuzzy controller design problem for a phugoid model-based multi-agent system. The error between the state of a phugoid model and a reference is defined to construct a multi-agent system model. A T-S fuzzy model of the multi-agent system is built by introducing a nonlinear controller. A fuzzy controller is then designed to stabilize the T-S fuzzy model, where the synthesis condition is represented in terms of linear matrix inequalities.