• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.248-254
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• 2000

This paper presents and output feedback fuzzy H(sup)$\infty$ control problem for a class of nonlinear systems with time-varying delayed state. The Takagi-Sugeno fuzzy model is employed to represent a nonlinear systems with time-varying delayed state. Using a single quadratic Lyapunov function, the globally exponential stability and disturance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of fuzzy H(sup)$\infty$ controllers are given in terms of matrix inequalities. Constructive algorithm for design of fuzzy H(sup)$\infty$ controller is also developed. A simulation example is given to illustrate the performance of the proposed design method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.465-465
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• 2000

The paper presents the fuzzy control technique to adjust the gain schedule in the fuzzy controller. The micro computer is designed to the fuzzy controller to execute the proportional gain with the data of the error and speed command. The gain schedule is the fuzzy set which execute based on the fuzzy rule. The gain schedule from the fuzzy controller is fed to the sinusoidal pulse width modulation (SPWM) inverter for control the response and speed of the induction motor. The induction motor coupling to the DC motor and tachogenerator which DC motor as a load. The test result of the fuzzy control technique in the open loop control, it provides a good response and in the closed loop control it can control speed in the any condition of load design

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.187-193
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• 2003

In this paper, a systematic design method of the intelligent PAM fuzzy controller for nonlinear systems using the efficient tools-Linear Matrix Inequality and the intelligent digital redesign is proposed. In order to digitally control the nonlinear systems, the TS fuzzy model is used for fuzzy modeling of the given nonlinear system. The convex representation technique also can be utilized for obtaining TS fuzzy models. First, the analog fuzzy-model-based controller is designed such that the closed-loop system is globally asymptotically stable in the sense of Lyapunov stability criterion. The simulation results strongly convince us that the proposed method has great potential in the application to the industry.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.559-564
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• 2002

This Paper Proposes a design method of a fuzzy output feedback controller for the nonlinear systems with the unknown time- delay. Recently, Cao et ai. proposed a stabilization method for the nonlinear time-delay systems using a fuzzy controller when the time-delay is known. However, the time-delay is likely to be unknown in practical. We represent the nonlinear systems with the unknown time-delay by Takagi-Sugeno (T-5) fuzzy model and design the fuzzy observer and the parallel distributed compensation (PDC) law based on this observer. By applying Lyapunov-Krasovskii theorem to the closed-loop system, the sufficient condition for the asymptotic stability of the equilibrium Point is derived and converted into the linear matrix inequality (LMI) Problem.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.127-137
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• 2006

This paper presents an $H_{\infty}$ controller synthesis method for discrete time fuzzy dynamic systems based on a piecewise smooth Lyapunov function. The basic idea of the proposed approach is to construct controllers for the fuzzy dynamic systems in such a way that a Piecewise smooth Lyapunov function can be used to establish the global stability with $H_{\infty}$ performance of the resulting closed loop fuzzy control systems. It is shown that the control laws can be obtained by solving a set of Bilinear Matrix Inequalities (BMIs). An example is given to illustrate the application of the proposed method.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.95-105
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• 2001

In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model(SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied for the control of an uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control(CMFC).

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.851-856
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• 2011

In this paper, the fuzzy output-feedback controller is addressed for a discrete-time nonlinear interconnected systems with common input. The nonlinear interconnected system is represented by a T-S (Takagi-Sugeno) fuzzy model. Based on T-S fuzzy interconnected system, the fuzzy output-feedback controller is designed with common input. The stability condition of the closed-loop system is represented to the LMI (Linear Matrix Inequality) form. PEMFC model is given to show the verification of the controller discussed throughout the paper.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.145-150
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• 2005

We proposed the indirect adaptive fuzzy model based sliding mode controller to control nonaffine nonlinear systems. Takagi-Sugano fuzzy system is used to represent the nonaffine nonlinear system and then inverted to design the controller at each sampling time. Also sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. The proposed controller and adaptive laws guarantee that the closed-loop system is stable in the sense of Lyapunov and the output tracks a desired trajectory asymptotically.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.390-392
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• 2009

This paper is concerned with the stabilization problem of nonlinear networked control 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 fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. Based on a stocastic 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.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.329-331
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• 2009

This paper is concerned with the stabilization problem of nonlinear networked control 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 fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. Based on a stocastic 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.