• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.267-272
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• 2012

This paper propose the implementation of robust fuzzy controller for controlling an active magnetic bearing (AMB) system with 6 degree of freedom (DOF). A basic model with 6 DOF rotor dynamics and electromagnetic force equations for conical magnetic bearings is proposed. The developed model has severe nonlinearity and uncertainty so that it is not easy to obtain the control objective. For solving this problem, we use the Takagi-Sugeno (T-S) fuzzy model which is suitable for designing fuzzy controller. The control object in the AMB system enables the rotor to rotate without any phsical contact by using magnetic force. In this paper, we analyze the nonlinearity of the active magnetic bearing system by using fuzzy control algorithm and desing the robust control algorithm for solving the parameter variation. Simulation results for AMB are demonstrated to visualize the feasibility of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.321-324
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• 2003

This paper discusses a robust stochastic stabilization of uncertain 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 discretixzd T-S fuzzy system is represented by a uncertain discrete-time T-S fuzy system with jumping parameters. The robust stochastic stabilizibility of the uncertain jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs).

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2815-2817
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• 2005

This paper presents an experiment study on the control of a rotary-type inverted pendulum based on the Takagi-Sugeno (T-S) fuzzy model approach. A sufficient condition for stability of the T-S fuzzy control system is given via linear matrix inequalities (LMIs). State-feedback controllers for sub-systems are designed from the sufficient condition via change of variables which is one of the popular LMI techniques. Experimental results on a rotary-type inverted pendulum control show the feasibility of the T-S fuzzy model-based control method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.973-981
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• 2012

In this paper, it suggest that nonlinear multivariable system control of induction motor using 'T-S Fuzzy Identification' 'T-S Fuzzy model of linearization' is not easy because of that arithmetic is difficult in computation of the function. Therefore 'T-S Fuzzy Identification' is suggested that the rules and functions through the estimation of high accuracy provides linearized model.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.323-328
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• 2009

In this paper, a decentralized fuzzy output feedback controller for the nonlinear networked control system is proposed for wireless sensor network. Especially, it is assumed that the networked control system has the output packet loss and the input transmission failure. For the fuzzy control of the nonlinear subsystem, it presents Takagi-Sugeno (T-S) fuzzy model of each subsystem and it designs the decentralized fuzzy output feedback controller. The stability condition of the closed-loop system with the proposed controller is obtained by Lyapunov functional. The obtained stability condition is represented to the linear matrix inequality (LMI) form, and the control gain is obtained by LMI. An example is given to show the verification discussed throughout the paper.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2516-2518
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• 2004

This paper proposes a stability condition in discrete-time affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties and then, introduces the design method of a fuzzy-model-based controller which guarantees the stability. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of linear matrix inequalities (LMIs).

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.185-190
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• 2009

In this paper, an observer-based intelligent controller for the nonlinear networked control systems with packet loss is proposed for wireless sensor network. For the intelligent control of the nonlinear system, it uses the fuzzy system with Takagi-Sugeno (T-S) fuzzy model. The observer is designed for the fuzzy networked control system, and the output feedback controller is proposed for the stability of estimates and errors. 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 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.16 no.2
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• pp.138-143
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• 2006

This paper presents intelligent digital redesign method for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an . example to guarantee the stability and effectiveness of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.1-6
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• 2004

This paper deals with a balanced model reduction for T-S(Takagi-Sugeno) fuzzy systems with time varying state delay. We define a generalized controllability gramian and a generalized observability gramian for a stable T-S fuzzy delayed systems. We obtain a balanced state space realization using the generalized controllability and observability gramian and obtain a reduced model by truncating states from the balanced state space realization. We also present an upper bound of the approximation error. The generalized controllability gramian and observability gramian can be computed from solutions of linear matrix inequalities. We demonstrate the efficacy of the suggested method by illustrating a numerical example.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.373-376
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• 2008

본 논문은 퍼지 펄스 폭 변조 (Pulse-width-modulation: PWM) 시스템의 안정도에 대해 다루게 된다. 복잡성을 가진 비선형 시스템은 Takagi-Sugeno (T-S) 퍼지 모델에 의해 효율적으로 논의될 수 있다. 본 논문에서는 기존의 LTI 시스템에서 논의 되었던 PWM 제어기 설계 문제를 퍼지 시스템으로 확장시킴으로써 PWM 제어기에 대한 논의의 저변을 확대시키고자 한다. 또한, 리아푸노프 (Lyapunov) 안정도에 기반 한 안정도 증명을 통해 퍼지 PWM 시스템의 안정도를 분석하고자 한다.