• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.140-143
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• 2001

In this paper, a control problem of the Takagi-Sugeno(TS) fuzzy system with time-varying input delay is considered. It is well known that the delay is one of the major sources responsible for the instability of the controlled system. A systematic design technique is developed based on the Lyapunov-Razumikhin stability theorem. A sufficient condition for the global asymptotic stability of the TS fuzzy systems is formulated in terms of linear matrix inequalities (LMIs). The derived condition can deal with any time-varying input delay within the admissible bound. The effectiveness of the proposed controller design technique is demonstrated by a numerical simulation.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.583-595
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• 2008

In this paper, we introduce a fuzzy nonlinear feedback approach to the control of a class of chaotic dynamical systems. The fuzzy Parallel Distributed Compensation with Reduced Rule Base approach (PDC_RRB) is proposed. The design procedure is conceptually simple and considered to a nonlinear optimal and robust control problem due to the nonlinear nature of the Takagi-Sugeno (TS) fuzzy system. Simulation results are provided to show the effictiveness of the proposed methodology.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.35.2-35
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• 2002

$\textbullet$ Introduction $\textbullet$ An affine fuzzy system $\textbullet$ The stabilization of an affine fuzzy system $\textbullet$ Iterative LMI algorithm for the stabilization $\textbullet$ A numerical example $\textbullet$ Conclusion

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.449-452
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• 1997

In this paper, we suggest a variable structure controller using the time-varying nonlinear sliding surface instead of the fixed sliding surface, which has been the robustness against parameter variations and extraneous disturbance during the reaching phase. As appling TS fuzzy algorithm to the regulation of the nonlinear sliding surface, the reaching time of the system trajectory is faster than the fixed method . This proposed scheme has better performance than the conventional method in reaching time parameter variation and extraneous disturbance. To demonstrate its performance, the proposed control algorithm is applied to a rotational inverted pendulum.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.407-414
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• 2000

This paper addresses the analysis and design of fuzzy control systems for a class of complex uncertain single-input single-output nonlinear systems. The proposed method represents the nonlinear system using a Takagi-Cugeno fuzzy model and construct a global fuzzy logic controller by blending all local state feedback controllers with a sliding mode controller. Unlike the commonly used parallel distributed compensation technique, we can design a global stable fuzzy controller without finding a common Lyapunov function for all local control systems, and can obtain good tracking performance by using sliding mode control theory. Furthermore, stability analysis is carried out not for the fuzzy model but for the real nonlinear system with uncertainties. Duffing forced oscillation sysmte is used as an example to show the effectiveness and feasibility of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.225-235
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• 2005

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 in 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.15 no.3
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• pp.318-323
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• 2005

In this paper, we propose a systematic method of a fuzzy-model-based controller for continuous-time nonlinear dynamical systems which may contain uncertainties. The continuous-time uncertain TS fuzzy model is first constructed to represent the uncertain nonlinear system. A parallel distributed compensation (PDC) technique is then used to design a fuzzy model based controller for both stabilization and tracking. Finally, the designed continuous-time controller is converted to an equivalent discrete-time controller by using an intelligent digital redesign method. This new design technique provides a systematic and effective framework for integration of the fuzzy model based control theory and the advanced digital redesign technique for nonlinear dynamical systems with uncertainties. Finally, the single link flexible-joint robot arm is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2398-2400
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• 2000

In this paper, we consider multi-objective synthesis of fuzzy controllers for a widely used special class of the Takagi-Sugeno(TS) fuzzy systems. We propose a new fuzzy controller utilizing the strategy of rescaling and show that synthesis of the proposed controllers satisfying multiple design objectives can be reduced to a simple linear matrix inequality(LMI) problem. Finally, an application to an inverted pendulum on a cart is presented to illustrate the validity of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.130-135
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• 2007

In this paper, a direct model reference adaptive fuzzy control (MRAFC) scheme is developed for the plant model whose structure is represented by the MIMO Takagi-Sugeno fuzzy model. The MRAFC scheme is proposed to provide asymptotic tracking of a reference signal lot the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee that all signals in the closed-loop system are bounded. In addition, the plant state tracks the state of the reference model asymptotically with time tot any bounded reference input signal.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.87-93
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• 1999

This paper proposes a systematic designs methodology for the Takagi-Sugeno (TS) model based fuzzy control systems with guaranteed stability and pre-specified transient performance for the application to a nonlinear magnetic bearing system. More significantly, in the proposed methodology , the control design problems which considers both stability and desired transient performance are reduced to the standard LMI problems . Therefore, solving these LMI constraints directly (not trial and error) leads to a fuzzy state-feedback controller such that the resulting fuzzy control system meets above two objectives. Simulation and experimentation results show that the proposed LMI-based design methodology yields only the maximized stability boundary but also the desired transient responses.