• Journal of Institute of Control, Robotics and Systems
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• 제17권9호
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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.

• Journal of the Korean Institute of Telematics and Electronics C
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• 제35C권3호
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• pp.90-96
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• 1998

The self-excited oscillation is the phenomenon which can be observed in the systems composed of nonlinear elements. The phenomenon is of fundamental importance in nonlinear systems and, as far as the design of a nonlinear system is concerned, it should be considered along with the stability analysis. In this paper, the oscillation of a system controlled by a static nonlinear fuzzy controller is theoretically addressed. First, the describing functionof a static fuzzy controller is derived and then, based on the derived describing function, self-excited oscillation of the system controlled by a static fuzzy controller is predicted. To obtain the describing function of the static fuzzy controller, a simple struture is assumed for the fuzzy controller. Finally, computer simulation is included to show an example where the describing function given in the paper is used to predict the self-excited oscillation of a fuzzy-control system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.39-42
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• 2001

This paper we study the exact controllability for the nonlinear fuzzy control system in E$^{2}$$_{N}$ by using the concept of fuzzy number of dimension 2 whose values are normal, convex, upper semicontinuous and compactly supported surface in R$^{2}$.>.

• Proceedings of the KIEE Conference
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2302-2304
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• 2000

This paper addresses a fuzzy controller for nonlinear systems control using a pole placement in a specified disk. In the method, we linearize a nonlinear plant about nominal operating points and represent it using TS fuzzy model and formulate the controller rules. A feedback control law for a local model is determined using a pole placement in a specified disk(${\alpha}$:center ${\gamma}$:radius} region so that the closed loop system is stable. A nonlinear system can be controlled by combining fuzzy controller with a pole placement scheme which can be used to modify the transient response such as damping ratio and overshoot. A stability of overall fuzzy control system is guaranteed in the Lyapunov sense. Finally, it is shown that the proposed method is feasible through a computer simulation.

• Proceedings of the KIEE Conference
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.510-512
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• 1999

In this paper, we present a method for the analysis and design of fuzzy controller for nonlinear systems. In the design procedure, we represent the dynamics of nonlinear systems using a Takagi-Sugeno fuzzy model and formulate the controller rules, which shares the same fuzzy sets with the fuzzy system, using parallel distributed compensation method. Then, after the feedback gain of each local state feedback controller is obtained using the existing optimal pole-placement scheme, we construct an overall fuzzy logic controller by blending all local state feedback controller. Finally, the effectiveness and feasibility of the proposed fuzzy-model-based controller design method has been evaluated through an inverted pendulum system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.220-226
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• 2002

In this paper, we develop the intelligent digitally redesigned fuzzy controller for nonlinear systems. Takagi-Sugeno (TS) fuzzy model is used to model the nonlinear systems and a continuous-time fuzzy-model-based controller is designed based on the extended parallel-distributed-compensation(EPDC) method . The digital controllers are determined from existing analogue controllers. The proposed method provides an accurate and effective method for digital control of continuous-time nonlinear systems and enables us to efficiently implement a digital controller via the pre-determined continuous-time 75 fuzzy-model-based controller. We have applied the proposed method to the duffing forced oscillation system to show the effectiveness and feasibility of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권1호
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• pp.15-20
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• 2006

In this paper we study the exact controllability for the nonlinear fuzzy control system with nonlocal initial condition in $E_N^n$ by using the concept of fuzzy number of dimension n whose values are normal, convex, upper semicontinuous and compactly supported surface in $R^n$. $E_N^n$ be the set of all fuzzy numbers in $R^n$ with edges having bases parallel to axis $X_1,X_2,\;,X_n$.

• Smart Structures and Systems
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• 제11권3호
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• pp.315-329
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• 2013

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.198-198
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• 2000

In this paper, the linearization method of nonlinear systems via fuzzy controllers which can be the basic research for designing a systematic fuzzy controllers with singleton consequents is proposed. We regard a closed loop system as a canonical form and propose a methodology for linearization of nonlinear system which adjust the input at vertex using zero condition and affinity condition. Through some examples, we show the validity of the proposed method and it can be extended to the design problem of fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.86-86
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• 2000

This paper describes a neural network based fuzzy type PID control scheme. The PID controller is being widely used in industrial applications. however, it is difficult to determine the appropriate PID gains for (he nonlinear system control. In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a neural network based fuzzy type PID controller whose scaling factors were adjusted automatically. The value of initial scaling factors of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods and then they were adjusted by using neural network control techniques. Proposed controller was simple in structure and computational burden was small so that on-line adaptation was easy to apply to. The result of practical experiment on the magnetic levitation system, which is known to be hard nonlinear, showed the proposed controller's excellent performance.