• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.300-305
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• 2004

This paper concerns controller design for the Takagi-Sugeno (TS) fuzzy systems. The design method proposed in this paper is derived in the framework of the optimal control theory utilizing the piecewise quadratic optimal value functions. The major part of the proposed design procedure consists of solving linear matrix inequalities (LMIs). Since LMIs can be solved efficiently within a given tolerance by the recently developed interior point methods, the design procedure of this paper is useful in practice. A design example is given to illustrate the applicability of the proposed method.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.485-488
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• 2002

In this paper, fuzzy logic controllers are designed for compensation of distance errors. Because we can't know information of the depth in a mono camera, these errors are occurred. Also, they are increased as a target object is to keep away from a center of image. Therefore, the errors for each position of joints of an arm robot should be modeled, but accurate models can't be obtained because of no information of the depth, uncertain feature points of image, parameter uncertainties, and illumination. Hence, fuzzy logic controllers for each error are designed for compensation. This paper consists of color image processing, error modeling, and the controller design. Experimental results are given to verify the effectiveness of our proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.110-110
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• 2000

In this paper, an antilock brake system (ABS) for commercial vehicles is studied by considering the design of a fuzzy Logic controller with pulse width modulation (PWM). PWM method is used for generating solenoid valve inputs in order to cope with the chattering problem caused by the conventional on/off control The sliding mode observer is designed to estimate the vehicle longitudinal velocity and it is used to calculate the wheel slip ratio. The effectiveness of the proposed control algorithm was validated by simulations performed with a nonlinear 14-DOF vehicle model including the dynamics of the brakes.

• Journal of information and communication convergence engineering
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• v.3 no.1
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• pp.43-48
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• 2005

In this paper, the adaptive fuzzy logic controller(AFLC) is proposed, which uses real-coding genetic algorithm showing a good performance on convergence velocity and diversity of population among evolutionary computations. The effectiveness of the proposed AFLC was demonstrated by computer simulation for speed control system of AC servo motor. As a result of simulation for the AC servo motor, it is shown the proposed AFLC has the better performance on overshoot, settling time and rising time than the PI controller which is used when tuning AFLC.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.196-198
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• 2005

In this paper, we design the Thyristor Controlled Series Capacitor(TCSC) supplementary controller for oscillation damping of power system. Here the supplementary controller is designed as a fuzzy logic-based precompensation approach for TCSC. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing TCSC. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Simulation results show that the proposed control technique is superior to a conventional method in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.646-651
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• 2004

This paper deals with a new adaptive fuzzy sliding mode controller and its application to an inverted pendulum. We propose new method of adaptive fuzzy sliding mode control scheme that the fuzzy logic system is used to approximate the unknown system functions in designing the SMC of uncertain nonlinear systems. The controller's construction and its analysis involve sliding modes. The proposed controller consists of two components. 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. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum. The results show that both alleviation of chattering and performance are achieved

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.197-197
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• 2000

In this paper, we present a novel method for design of fuzzy Logic controllers by defining a set of characteristic parameters (CFLCS). These parameters are extracted and defined by examining the structure and characteristics of the individual components of FLCs and parameterizing those. Based upon this formulation, a series of simulations is conducted for plants having simple dynamics in order to see the performance of this proposed method. The simplicity and effectiveness of this method are discussed in detail.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.414-416
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• 1998

One significant error in XY table is due to friction and disturbance. However, the characteristics of this friction is not easy to predict and analyze because of its nonlinearity. Therefore, it is difficult for conventional controller to compensate it effectively. In order to solve this problem, this paper presents a position controller based on fuzzy logic controller(FLC) that is suitable for system with unknown and unmodelled dynamics. The performance of the proposed controller are demonstrated by simulation results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.191-196
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• 1998

A new Fuzzy Logic Controller(FLC) called a Gradient-Descent Based Self-Organizing Controller is presented. The Self-Organizing Controller(SOC) has two inputs such as error and change of error, and updates control rules with monitoring a performance measure. There are many works in the SOC which concentrate on the self-organizing ability in control rule base, but have a few research on the performance measure which is akin to sliding mode control. With this procedure, we can get a robust performance measure on the SOC. To verify the perfomance of proposed controller, we have performed for the cart-pole system which is one of the well-known benchmark problem in the control literature.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.221-223
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• 2000

This paper describes the design of SVC fuzzy logic controller (SVC-FLC) using adaptive evolutionary algorithm and we tuned the gain of input-output variables of SYC-FLC using it. We performed the nonlinear simulation on an single-machine infinite system to prove the efficiency of the proposed method. The proposed SYC-FLC showed the better performance than PD controller in terms of the settling time and damping effect, for system operation condition used in evaluating the robustness and three phase grounding default in cases of nominal loading used in tuning SVC-FLC for a single-machine infinite system.