• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.310-312
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• 1996

In this paper, we propose a design method for nonlinear SISO system using Takagi-Sugeno fuzzy model and Genetic Algorithm. Our method can reduce the number of design parameters and has advantage of small search space of Genetic Algorithm. The proposed nonlinear controller, which can be implemented by fuzzy controller and simple nonlinear controller, cancels the original nonlinear dynamics and gives the optimal nonlinear dynamics. We illustrated the performance of the proposed controller by simple simulation example.

• 제어로봇시스템학회논문지
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• 제22권1호
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• pp.40-45
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• 2016

This paper presents the neuro-fuzzy control method for balancing a two-wheel mobile robot. A two-wheel mobile robot is built for the experimental studies. On-line learning algorithm based on the back-propagation(BP) method is derived for the Takagi-Sugeno(T-S) neuro-fuzzy controller. The modified error is proposed to learn the B-P algorithm for the balancing control of a two-wheel mobile robot. The T-S controller is implemented on a DSP chip. Experimental studies of the balancing control performance are conducted. Balancing control performances with disturbance are also conducted and results are evaluated.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.142-145
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• 2000

A new robust load-frequency control (LFC) methodology is proposed for nonlinear power systems with the valve position limits of the governor in the presence of parametric uncertainties. The Takagi-Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the nonlinear power system. A sufficient condition of the robust stability is presented in the sense of Lyapunov for the TS fuzzy model with parametric uncertainties. The intelligent digital redesign technique for the uncertain nonlinear power system is also studied. The effectiveness of the proposed robust fuzzy LFC controller design method is demonstrated through a numerical simulation.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.123-128
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• 1998

This paper proposes design of LFT-based fuzzy controllers for model-following, which are better than the previous input-output linearization controllers, which are not able to follow the model system states and which do not guarantee the stability of all states. The method proposed in this paper provides a LFT-based Takagi-Sugeno(T-S) fuzzy controller with guaranteed stability and model-following via the following steps: First, using LFT(Linear Fractional Transformation) and T-S fuzzy model, controllers, are obtained. Next, error dynamics are obtained for model-following, and errors go to 0(zero). Finally, a T-s fuzzy controller that can stabilizxe the system with the requirement on the control input satisfied is obtained by solving the LMIs with the MATLAB LMI Control Toolbox and a model-following controller is obtained. Simulations are performed for the LFT-based T-S fuzzy controller designed by the proposed method, which show better performance than the results of input-out ut linearization controller.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.84-87
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• 2002

This paper presents an adaptive PID control scheme with fuzzy model for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model was used to estimate the error of control input, and the parameter of PID controller was adapted from the error The parameter of TSK fuzzy model was also adapted to plant by comparing the activity output of plant and model output. PID controller which was adapted the uncertainty of nonlinear plant and the change of parameter can be designed by using the presented method. The usefullness of algorithm which was proposed by the simulation of several nonlinear system was also certificated.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.126-129
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• 2002

An intelligent digital redesign technique (IDR) for the observer-based output feedback Takagi-Sugeno (T-5) fuzzy control system with fuzzy outputs is developed. The considered IDR condition is cubically parameterized as convex minimization problems of the norm distances between linear operators to be matched.'rho stability condition is easily embedded and the separations principle is explicitly shown.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.379-381
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• 2004

In this paper, a robust $H_{\infty}$ stabilization problem to a uncertain fuzzy systems with time-varying delay via static output feedback is investigated. The Takagi-Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear systems with time-varying delayed state. Using a single Lyapunov function, the globally asymptotic stability and disturbance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust $H_{\infty}$ controllers are given in terms of linear matrix inequalities.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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• pp.235-236
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• 2008

This paper is concerned with the stabilization problem of Markovian jump nonlinear systems with time-delay via Takagi-Sugeno (T-S) fuzzy control approach. The T-S fuzzy models are employed to represent nonlinear systems with Markovian jump parameters and time-delay. The purpose of this paper is to design a mode-independent fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. Based on a stochstic Lyapunov function, stabilization sufficient conditions using a mode-independent fuzzy controller are derived for the Markovian jump fuzzy system in terms of Linear Matrix Inequalities (LMIs). Finally, a simulation example is presented to illustrate the effectiveness of the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.697-699
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• 2000

In this paper, an extension of model predictive controller for nonlinear process using Takagi-Sugeno(TS) fuzzy model is proposed Since the consequent parts of TS fuzzy model comprise linear equations of input and output variables. it is locally linear, and the Generalized Predictive Control(GPC) technique which has been developed to control Linear Time Invariant(LTI) plants, can be extended as a parallel distributed controller. Also fuzzy soft constraints are introduced to handle both equality and inequality constraints in a unified form. So the traditional constrained GPC can be transferred to a standard fuzzy optimization problem. The proposed method conciliates the advantages of the fuzzy modeling with the advantages of the constrained predictive control, and the degree of freedom is increased in specifying the desired process behavior.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.110-112
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• 2000

A new robust digital fuzzy controller design methodology is proposed for load frequency of nonlinear power system with valve position limits of governor in the presence of parametric uncertainties. The Takagi-Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the nonlinear power system. A sufficient condition of robust stability for robust fuzzy control with parametric uncertainties is presented in the sense of Lyapunov. The controller that designed by preposed robust fuzzy controller design method is based compounding condition between continues system and discrete system. The effectiveness of controller that designed by the proposed robust fuzzy controller design method is demonstrated through simulation example.