• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.255-257
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• 1992

The expert system described in this article tunes a proportional-integral-derivative(PID) controller for a single-input single-ouput process. The expert system examines features of each transient response and the corresponding controller parameters. It determines a new set of controller gains to obtain a more desirable time reponse using fuzzy logic. This technique can be used to determine and implement a different set of PID gains for each operating regime and, once in steady state, the system can be used to find optimal parameters for load disturbance rejection.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.4
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• pp.54-60
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• 2001

This paper deals with control design method having anticipation delay which is proposed for the discrete nonlinear engine where system dynamics is not accurate. Due to the induction-to-power delay in internal combustion(IC) engine having abrupt torque loss, underdamping and chattering in engine idle speed becomes a serious problem and it could make drivers uncomfortable. For this reason, Three types of the closed-loop controller are developed for the stable engine idle speed control. The inputs of the controllers are an engine idle speed and air conditioning signal. The output of the controllers is an duty cycle to operate the idle speed control valve(ISCV). The proposed controllers will be useful for improving actual vehicles since these shows good test

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1141-1143
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• 1997

This paper presents a design technique of the FPID controller for the load frequency control of power system. parameters of FPID controller are self-tuned by the fuzzy inference algorithm. The computer simulation results show that the proposed controller are more excellent control characteristics than conventional in transient-state and steady-state response.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.480-489
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• 1999

Design and experimental results of yaw rate controller is described for electricallydriven four wheel vehicle without steering mechanism. Yaw rate controller has been known to be necessary to cope with nonlinear char-acteristics of the wheel/road conditions with respect to different road condition and steering angle. For an effective yaw rate control, a fuzzy PID gain scheduler is considered with changing control parameters. In order to apply proposed algorithm to the system a downsized four wheel drive electrically driven vehicle without steering mechanism was manufactured. With these techniques the proposed yaw rate controller is shown by experiment results to be obtained suficient performance in the whole steering regions.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.134-134
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• 2000

A switching control using multiple gains in the fuzzy rule is newly proposed for an abruptly changing hydraulic servo system. The proposed scheme employs fuzzy PID control, where modified input parameters are used, and LVQNN(Learning Vector Quantization Neural Network) as a switching controller (supervisor). Simulation and experimental studies have been carried out to validate and illustrate the proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.735-743
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• 2010

A new Fuzzy sliding mode controller is proposed to improve the cornering performance of the four wheel hybrid vehicles. The Fuzzy sliding mode control is applied for the control of rear motor and EHB (Electro-Hydraulic Brake) to improve the cornering performance. The modeling of the automobile is simplified that each of the two wheels is modeled as two degrees of freedom object and the friction coefficient between the wheel and the ground is assumed to be constant. The output of the Fuzzy sliding mode algorithm is the direct yaw moment for the rear wheels, which compensates for the slip angle. Through the simulations using ADAMS and MATLAB Simulink, the cornering performance of the proposed algorithm is compared to the conventional PID to show the superiority of the proposed algorithm. In the simulation experiments, the J-Turn and single lane change are used for each of the Fuzzy sliding mode algorithm and PID controller with the optimal gains which are tuned empirically.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.2
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• pp.48-54
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• 2002

In this study, a neuro-fuzzy controller which has the characteristic of fuzzy control and artificial neural network is designed. A fuzzy rule to be applied is automatically selected by the allocated neurons. The neurons correspond to fuzzy rules are created by an expert. To adapt the more precise model is implemented by error back-propagation learning algorithm to adjust the link-weight of fuzzy membership function in the neuro-fuzzy controller. The more classified fuzzy rule is used to include the property of dual mode method. In order to verify the effectiveness of the proposed algorithm designed above, an operating characteristic of a DC servo motor with variable load is investigated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.350-353
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• 2003

In this paper, we proposed the method to design fuzzy controller using the experience of the operating expert and experimental numeric data for the robust control about the noise and disturbance instead of the traditional PID controller for the main steam temperature control of the thermal power plant. The temperature of main steam temperature process has to be controlled uniformly for the stable electric power output. The process has the problem of the hunting for the cases of various disturbances. In that case, the manual action of the operator happened to be introduced in some cases. We adopted the TSK (Takagi-Sugeno-Kang) model as the fuzzy controller and designed the fuzzy rules using the informations extracted directly from the real plant and various operating condition to solve the above problems and to apply practically. We implemented the real fuzzy controller as the Function Block module in the DCS(Distributed Control System) and evaluated the feasibility through the experiment81 results of the simulation.

• International Journal of Aeronautical and Space Sciences
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• v.5 no.1
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• pp.30-38
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• 2004

This paper deals with a problem of automatic landing guidance and control ofthe longitudinal airplane motion under the wind shear turbulence. Adaptive gainscheduled PID control law is proposed in this paper. Fuzzy logic is the main part ofthe adaptive PID controller as gain scheduler. To illustrate the successful applicationof the proposed control law to the automatic landing control problem, numericalsimulation is carried out based on the longitudinal nonlinear airplane model excited bythe wind shear turbulence. The simulation results show that the automatic landingmaneuver is successfully achieved with the satisfactory performance and the gainadaptation of the control law is made adequately within the limited gains.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.152-157
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• 2001

This paper presents the design method of the new controller for looper system in hot strip finishing mill. Looper response time is related to the performance of the tension control to reduce the delivery width error. The quality of the hot strip product, especially width deviation at the top of the strip, is influenced greatly by the precision of tension control. In this paper, a new fuzzy PID control system is designed to obtain the fast looper angle response and the high control precision. The computer simulation to verify the performance of the new controller is executed. From the results of the simulation, the tension control can obtain better performance than that of the conventional PID case.