• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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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.

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

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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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.

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

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.199-204
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• 2004

In this paper, a new dual-rate digital control technique for the Takagi-Sugeno (T-S) fuzzy system is suggested. The proposed method takes account of the stabilizablity of the discrete-time T-S fuzzy system at the fast-rate sampling points. Our main idea is to utilize the lifted control input. The proposed approach is to obtain the dual-rate discrete-time T-S fuzzy system by discretizing the overall dynamics of the T-S fuzzy system with the lifted control, and then to derive the sufficient conditions for the stabilization in the sense of the Lyapunov asymptotic stability for this system. An example is provided for showing the feasibility of the proposed discretization method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.672-677
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• 2004

In this paper, a new dual-rate digital control technique for the Takagi-Sugeno (T-S) fuzzy system is suggested. The proposed method takes account of the stabilizablity of the discrete-time T-S fuzzy system at the fast-rate sampling points. Our main idea is to utilize the lifted control input. The proposed approach is to obtain the dual-rate discrete-time T-S fuzzy system by discretizing the overall dynamics of the T-S fuzzy system with the lifted control, and then to derive the sufficient conditions for the stabilization in the sense of the Lyapunov asymptotic stability for this system. An example is provided for showing the feasibility of the proposed discretization method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.4
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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.

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

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

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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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.