• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.36C no.7
• /
• pp.56-64
• /
• 1999

In this paper, a novel approach to the stability analysis of the continuous affine Takagi-Sugeno fuzzy control systems is proposed. The suggested analysis method is easily implemented by the recently spotlighted convex optimization techniques called Linear Matrix Inequalities (LMI). First, it derives the stability condition under which the affine Takagi-Sugeno fuzzy system is stable in the large. Next, the derived condition is recast in the formulation of LMI and numerically addressed. Finally, the applicability of the suggested methodology is highlighted via computer simulations.

• Proceedings of the IEEK Conference
• /
• 1999.11a
• /
• pp.1023-1026
• /
• 1999

In recent years, many studies have been conducted on fuzzy control since it can surpass the conventional control in several respects. In this paper, a novel approach to the stability analysis of the continuous-time affine Takagi-Sugeno fuzzy control system is proposed. The suggested analysis method is easily implemented by the recently spotlighted convex optimization techniques called Linear Matrix Inequalities (LMI).

• Proceedings of the KIEE Conference
• /
• 1999.07g
• /
• pp.2853-2855
• /
• 1999

본 논문은 TS(Takagi-Sugeno) 퍼지 모델로 표현된 비선형 시스템의 최적 퍼지 제어에 관한 새로운 설계 방법론을 제시하며, 최적 TS 퍼지 제어기의 매개 변수들을 설정하는 문제가 선형 행렬 부등식 문제로 표현될 수 있음을 보인다.

• Transactions on Control, Automation and Systems Engineering
• /
• v.4 no.4
• /
• pp.356-362
• /
• 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.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.7
• /
• pp.589-596
• /
• 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.

• Journal of Korea Water Resources Association
• /
• v.44 no.7
• /
• pp.537-551
• /
• 2011

Based on optimal input data combination selected in the earlier study, Neuro-Fuzzy flood forecasting model linked Takagi-Sugeno fuzzy inference theory with neural network in Wangsukcheon and Gabcheon is established. The established model was applied to Wangsukcheon and Gabcheon and water levels for lead time of 0.5 hr, 1 hr, 1.5 hr, 2.0 hr, 2.5 hr, 3.0 hr are forecasted. For the verification of the model, the comparisons between forecasting floods and observation data are presented. The forecasted results have shown good agreements with observed data. Additionally to evaluate quantitatively for applicability of the model, various statistical errors such as Root Mean Square Error are calculated. As a result of the flood forecasting can be simulated successfully without large errors in all statistical error. This study can greatly contribute to the construction of a high accuracy flood information system that secure lead time in medium and small streams.

• Journal of Korea Water Resources Association
• /
• v.44 no.7
• /
• pp.523-536
• /
• 2011

The objective of this study is to develop the data driven model for the flood forecasting that are improved the problems of the existing hydrological model for flood forecasting in medium and small streams. Neuro-Fuzzy flood forecasting model which linked the Takagi-Sugeno fuzzy inference theory with neural network, that can forecast flood only by using the rainfall and flood level and discharge data without using lots of physical data that are necessary in existing hydrological rainfall-runoff model is established. The accuracy of flood forecasting using this model is determined by temporal distribution and number of used rainfall and water level as input data. So first of all, the various combinations of input data were constructed by using rainfall and water level to select optimal input data combination for applying Neuro-Fuzzy flood forecasting model. The forecasting results of each combination are compared and optimal input data combination for real-time flood forecasting is determined.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1758-1759
• /
• 2011

본 논문은 비선형 시스템의 소속함수 의존성을 이용한 관측기 기반 퍼지 제어기 설계 기법을 제시한다. Takage-Sugeno (T-S)퍼지 모델링을 이용해 비선형 시스템을 퍼지 모델로 표현한다. 시스템의 안정화 조건은 소속함수의 의존성을 이용한 리아푸노프 안정도 해석 방법을 이용해 유도된다. 안정화 조건은 선형 행렬 부등식으로 표현되며, 부등식의 해를 이용해 제어기의 이득값을 구한다. 모의실험을 통해 설계된 제어기의 타당성을 검증한다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.4
• /
• pp.349-354
• /
• 2015

This paper presents the stability conditions of the Takagi-Sugeno (T-S) fuzzy sampled-data filter. The error system between the T-S fuzzy system and fuzzy filter is presented. In the sense of the Lyapunov stability analysis, the stability conditions are given, which can be represented in terms of linear matrix inequalities (LMIs). The proposed stability conditions utilize the different approach from the conventional methods, and have better performance than that of the conventional ones. The simulation example is given to show the effectiveness of the proposed method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.731-736
• /
• 2007

Vibration isolation equipments are mostly required in precise measurement and manufacturing system. Among all the vibration isolation system, air-spring is the most widely used equipment because of low resonant frequency and high damping ratio. In this study, Takagi-Sugeno fuzzy method is used to design an active vibration isolation system using air-spring, and compared the fuzzy method with passive control method and PID control method. Due to the non-linearity characteristics of air-spring, fuzzy controller was verified to be the most effective both in simulation and experiment.