• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.477-486
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• 2001

In this paper , we study the problem of designing TS(Takagi-Sugeno) fuzzy controllers for the systems that can be approximated or represented by the TS fuzzy model. The main strategy used in this paper is the inverse optimal approach, in which the cost function is determined later than the Lyapunov function and its corresponding control input satisfying the design requirements such as stability, decay rate, and robustness against uncertainty. This approach is useful because it yields controllers satisfying the inherent robustness of optimal controllers as well as the considered design goals. The design procedures established in this paper are all in the from of solving LMIs(Iinear matrix inequalities). Since the LMIs arising in the design procedures can be solved within a given tolerance by the interior point methods. the design method of the paper are efficient in practice. The applicability of the proposed design procedures is demonstrated by design examples.

• Proceedings of the KIEE Conference
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• 2007.10c
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• pp.185-188
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• 2007

본 논문에서는 수소이온교환막 연료전지의 퍼지 모델링 기법을 제안하였다. 수소이온교환막 연료전지는 가정용으로 공급이 적합한 연료전지로서 최근들어 많은 연구가 진행되고 있다. 연료전지 특성 모델은 이러한 연구에 중요한 역할을 하고 있으면 이 때문에 다양한 연료 전지 모델링 기법들이 제안되고 있다. 본 논문에서는 선형 행렬부등식 최적화기법을 기반 새로운 형태의 퍼지 모델링 기법이 제안되었다. 최종적으로 시뮬레이션을 통해 제안된 기법의 우수성을 확인하였다.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2630-2632
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• 2000

In this paper, a control technique of Takagi-Sugeno (TS) fuzzy systems with parametric uncertainties is developed. The uncertain TS fuzzy system is represented as an uncertain multiple linear system. The control problem of TS fuzzy system is converted into the stabilization problem of a uncertain multiple linear system. A sufficient condition for robust stabilization is obtained in terms of linear matrix inequalities (LMI). A Design example is illustrated to show the effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.520-525
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• 2003

This paper concerns a design methodology of observer-based output-feedback digital controller for Takagi-Sugeno(TS) fuzzy systems using intelligent digital redesign (IDR). The term of IDR involves converting an analog fuzzy-mode-based controller into an equivalent digital one in the sense of state-matching. The considered IDR problem is viewed as convex minimization problems of the norm distances between linear operators to be matched. The stability condition is easily embedded and the separations principle is explicitly shown.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.2
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• pp.68-73
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• 2000

This paper addresses the analysis and design of fuzzy control systems for a class of complex nonlinear systems. Firstly, the nonlinear system is represented by Takagi-Sugeno(TS) fuzzy model and the global controller is constructed by compensating each linear model in the rule of TS fuzzy model. The design of conventional TS fuzzy-model-based controller is composed of two processes. One is to determine the static state feedback gain of each local model and the other is to validate the stability of the designed fuzzy controller. In this paper, we propose an alternative methods for the design of TS fuzzy-model-based controller. The design scheme is based on the extension of conventional optimal control theory to the design of TS fuzzy-model-based controller. By using the proposed method, the design and stability analysis of the TS fuzzy model-based controller is reduced to the problem of finding the solution of a set of algebraic Riccati equations. And we use the recently developed interior point method to find the solution of AREs, where AREs are recast as the LMI formulation. A numerical simulation example is given to show the effectiveness and feasibiltiy of the proposed fuzzy controller design method.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.174-179
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• 2009

We consider the stabilization problem for a class of networked control systems with neutral type of time delays. The neutral type of time-delays occur in controller-to-actuator and sensor-to-controller. The Takagi-Sugeno (T-S) fuzzy model is employed to represent a nonlinear system with neutral type of time-delays. The stabilization via state-feedback is first addressed, and delay-range-dependent stabilization conditions are proposed in terms of linear matrix inequalities (LMIs). Finally, an application example will be given to show the merits and design a procedure of the proposed approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.469-474
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• 2011

This paper presents the intelligent tracking method for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. K-means clustering and TS fuzzy system are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by K-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. While calculating expected value, the non-linearity of the maneuvering target is recognized as linear one by dividing acceleration and the capability of Kalman filter is kept in the filtering process. The error for the non-linearity is compensated by approximated acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.881-886
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• 2005

This paper presents intelligent digital redesign method of global approach 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 tile 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 power series, 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 tile 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.337-342
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• 2009

This paper concerns delay-range-dependent robust stability and stabilization for time-delay nonliner system via T-S fuzzy model approach. The time delay is assumed to be a time-varying continuous function belonging to a given range. On the basis of a novel Lyapunov-Krasovskii functional, which includes the information of the range, delay-range-dependent stability criteria are established in terms of linear matrix inequality. It is shown that the new criteria can provide less conservative results than some existing ones. Moreover, the stability criteria are also used to design the stabilizing state-feedback controllers. Numerical examples are given to demonstrate the applicability of the proposed approach.