• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.6
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• pp.80-86
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• 2002

In this paper, we present a method of fuzzy controller design for the power plant superheater in the form of bilinear system. For the steam temperature control, the input variables are constructed by the area of difference between the profiles estimated from bilinear observer and reference profiles, and the time rate of change. We estimate the control rules by T. Takagi and M. Sugeno's fuzzy model. The feasibilities of the suggested method are illustrated via the computer simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.40.5-40
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• 2001

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-S) 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.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.24-30
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• 2024

This paper investigates the identification and modeling of a climate greenhouse. Given real climate data from greenhouse installed in the LAPER laboratory in Tunisia, the objective of this paper is to propose a solution of the problem of nonlinear time variant inputs and outputs of greenhouse internal climate. Based on fuzzy logic technique combined with least mean squares (lms) a robust greenhouse climate model for internal temperature prediction is proposed. The simulation results are presented to demonstrate the effectiveness of the identification approach and the power of the implemented Takagi-Sugeno Fuzzy model based Algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.60-65
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• 2008

In this paper, we concern the stability of smart space by using the robust digital controller. The proposed methodologies are based on the intelligent digital redesign (IDR). More precisely, we represent the nonlinear and uncertain analog system as the Takaki-Sugeno (T-S) fuzzy model. Then the IDR problem can be reduced to find the digital gains minimizing the norm distance between the closed-loop states of the analog and digital control. Its constructive conditions are expressed as the linear matrix inequalities (LMIs). At last, a numerical example, HVAC system, is demonstrated to visualize the feasibility of the proposed methodology.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.46-54
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• 1998

This paper presents a method for designing robust fuzzy $H^{\infty}$ controllers which stabilize nonlinear systems with parameter uncertainty adn guarantee an induced $L_{2}$ norm bound constraint on disturbance attenuation for all admissible uncertainties. Takagi and Sugeno's fuzzy models with uncertainty are used as the model for the uncertain nonlinear systems. Fuzzy control systems utilize the concept of so-called parallel distributed compensation(PDC). Using a single quadratic Lyapunov function, the stability condition satisfying decay rate and disturbance attenuation condition for Takagi and Sugeno's fuzzy model with parameter uncertainty are discussed. A sufficient condition for the existence of robust fuzzy $H^{\infty}$ controllers is then presented in terms of linear matrix inequalities(LMIs). Finally, design examples of robust fuzzy $H^{\infty}$ controllers for uncertain nonlinear systems are presented.

• 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.

• 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

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.135-138
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• 2002

본 논문에서는 비최소위상 시스템으로 표현되는 화력발전소 드럼의 수위제어를 위한 퍼지 제어기를 제안한다. 제안된 방법은 T. Takagi와 M. Sugeno의 퍼지모델을 기반으로 수행된다. 그리고 기존의 PID 및 LQ 제어기법을 적용한 방식과 비교하여 제안된 방법의 개선된 특성을 시뮬레이션 결과로부터 검증하였다.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.630-642
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• 2007

In this paper, we propose a direct model reference adaptive fuzzy control (MRAFC) for MIMO nonlinear systems whose structure is represented by the Takagi-Sugeno fuzzy model. The adaptive law of the MRAFC estimates the approximation error of the fuzzy logic system so that it provides asymptotic tracking of the reference signal for the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal. To verify the validity and effectiveness of the MRAFC scheme, the suggested analysis and design techniques are applied to the tracking control of robot manipulator and simulation studies are carried out. In the control design, the MRAFC is combined with feedforward PD control to make the actual joint trajectories of the robot manipulator with system uncertainties track the desired reference joint position trajectories asymptotically stably.

• 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.