• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.10
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• pp.1508-1512
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• 2012

This paper presents a relaxed stability condition for continuous-time affine fuzzy system using fuzzy Lyapunov function. In the previous studies, stability conditions for the affine fuzzy system based on quadratic Lyapunov function have a conservativeness. The stability condition is considered by using the fuzzy Lyapunov function, which has membership functions in the traditional Lyapunov function. Based on Lyapunov-stability theory, the stability condition for affine fuzzy system is derived and represented to linear matrix inequalities(LMIs). And slack matrix is added to stability condition for the relaxed stability condition. Finally, simulation example is given to illustrate the merits of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.560-564
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• 2015

This paper presents a design method of a static output feedback controller for continuous T-S fuzzy systems via parallel distributed compensation (PDC). The existence condition of a set of static output feedback gains is represented in terms of linear matrix inequalities (LMIs). The sufficient condition presented here does not need any transformation matrices and equality constraints and is less conservative than the previous results seen in [20].

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.496-501
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• 2016

This paper presents a design method of non-parallel distributed compensation (non-PDC) static output feedback controller for continuous- and discrete-time T-S fuzzy systems. The existence condition of static output feedback control law is represented in terms of linear matrix inequalities (LMIs). The proposed sufficient stabilizing condition does not need any transformation matrices and equality constraints and is less conservative than the previous result of [21].

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.788-791
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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, numerical stability analysis methodology for the singleton-type linguistic fuzzy control systems is proposed. The Proposed stability analysis is not the analytical method but the numerical method using the convex optimization technique of Quadratic Programming (QP) and Linear Matrix Inequalities (LMI).

• 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).

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.182-188
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• 2004

This paper presents a design method of delay-dependent control for T-S fuzzy systems with time delays. Based on parallel distributed compensation (PDC) and a descriptor model transformation of the system, a delay-dependent control is utilized. An appropriate Lyapunov-Krasovskii functional is chosen for delay-dependent stability analysis. A sufficient condition for delay-dependent control is represented in terms of linear matrix inequalities (LMIs).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.181-186
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• 2009

In this paper, the stability analysis for uncertain dynamic systems with time-varying delays is considered. By constructing a new Lyapunov functional, a novel stability criterion is established in terms of linear matrix inequalities (LMIs). Two numerical examples are carried out to support the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.270-270
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• 2000

Input delay is frequently encountered in the practical systems since measurement delay and computational delay can be represented by input delay. In this viewpoint, this paper deals with the robust control problem of input delayed systems with structured uncertainty. Robust stability conditions are provided in terms of linear matrix inequalities(LMIs) and it is shown that the proposed conditions can give less conservative maximum bound of input delay guaranteeing robust stability.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.159-164
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• 2017

In this paper, we propose a method of designing the sampled-data tracking controller for nonlinear systems expressed by the Takagi-Sugeno (T-S) fuzzy model. A sufficient condition that asymptotically stabilizes the state error between the linear reference model and the T-S fuzzy model is derived in terms of linear matrix inequalities. To this end, error dynamics are constructed, and the exact discretization method and the Lyapunov stability theory are employed in this paper. Finally, we validate the proposed method through the simulation example.