• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.7
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• pp.29-40
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• 2009

This paper proposes a modeling and controller design approach for a hybrid wind power generation system that considers a fixed wind-turbine and a dump load. Since operating conditions are kept changing, it is challenge to design a control for reliable operation of the overall system To consider variable operating conditions, Takagi-Sugeno (TS) fuzzy model is taken into account to represent time-varying system by expressing the local dynamics of a nonlinear system through sub-systems, partitioned by linguistic rules. Also, each fuzzy model has uncertainty. Thus, in this paper, a modem nonlinear control design technique, the sliding mode nonlinear control design, is utilized for robust control mechanism In the simulation study, the proposed controller is compared with a proportional-integral (PI) controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-hybrid power generation system.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.59-64
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• 2017

In this paper, a controller for discrete Takagi-Sugeno(T-S) fuzzy model under imperfect premise matching is proposed. Most of previous papers have obtained the stabilization condition using common quadratic Lyapunov function. However, the stabilization condition may be conservative due to the typical disadvantage of the common quadratic Lyapunov function. Hence, in order to solve this problem, we propose the stabilization condition of discrete T-S fuzzy model using fuzzy Lyapunov function. Finally, the proposed approach is verified by the simulation experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.45.1-45
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• 2002

$\textbullet$ Introduction $\textbullet$ Takagi-Sugeno Fuzzy Model and Sliding Mode Controller $\textbullet$ Observer and Controller Design $\textbullet$ Simulations $\textbullet$ References

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.582-589
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• 2003

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 Un 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.902-906
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• 2004

A separation principle of the Takagj-Sugeno (T-S) fuzzy-model-based observer-control is investigated. When the premise variables are able to be measured or directly computed from the outputs of the T-S fuzzy system and the fuzzy inference rules for the plant, control, and observer share the premise parts, the T-S fuzzy-model-based observer and the T-S fuzzy-model-based control can be separately designed such that the global stabilizability is guaranteed by the fuzzy observer-based output-feedback control. In this case, the global separation principle is well established. On the other hand, when the premise variables are unmeasurable or cannot be computed from the outputs, they should also be estimated. We examine the separation principle of this case. If the decay rates of the T-S fuzzy-model-based control and observer are sufficiently fast, the global separation is assured. Otherwise we show that the separation principle holds locally.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.780-785
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• 2007

This paper proposes the decentralized dynamic output feedback controller for discrete-time nonlinear interconnected systems using Takagi-Sugeno (T-S) fuzzy model. Through T-S fuzzy model of each subsystem, the decentralized dynamic output feedback controller is designed. By the closed-loop subsystems with controller, it represents the linear matrix inequality (LMI) for stability of whole interconnected system. The value of control gain are obtained by LMI. An example is given to show the experimentally verification discussed throughout the paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.423-429
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• 2011

This paper deals with the observer-based decentralized fuzzy controller design for nonlinear interconnected system for PEMFC. The nonlinear interconnected system is represented by a Takagi-Sugeno (T-S) fuzzy model. Based on T-S fuzzy interconnected system, the fuzzy observer and the decentralized fuzzy controller are designed. The stability condition of the closed-loop system with the proposed controller is represented to the linear matrix inequality (LMI) form, and the observer and control gain s are obtained by LMI. An example is given to show the verification discussed throughout the paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.174-179
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• 2009

We consider the stabilization problem for a class of networked control systems with neutral type of time delays. The neutral type of time-delays occur in controller-to-actuator and sensor-to-controller. The Takagi-Sugeno (T-S) fuzzy model is employed to represent a nonlinear system with neutral type of time-delays. The stabilization via state-feedback is first addressed, and delay-range-dependent stabilization conditions are proposed in terms of linear matrix inequalities (LMIs). Finally, an application example will be given to show the merits and design a procedure of the proposed approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.298-303
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• 2004

This paper deals with a stochastic stabilization of observer-based output-feedback control Takagi-Sugeno (T-S) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized T-S fuzzy system is represented by a discrete-time T-S fuzzy system with jumping parameters. The stochastic stabilizability of the jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs). The usefulness of the proposed algorithm is also certificated by simulation of 2 degree of freedom helicopter model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.129-132
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• 2001

In this paper, in order to control uncertain missile autopilot, an adaptive fuzzy control(AEC) scheme via parallel distributed compensation(PDC) is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy model. Moreover adaptive law is designed so that the plant output tracks the stable reference model(SRM), From the simulations results, we can conclude that the suggested scheme can effectively solve the control problems of uncertain missile systems based on T-S fuzzy model.