• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.73-78
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• 1996

In this study, we proposed a fuzzy gain scheduler with intelligent learning algorithm for a reactor control. In the proposed algorithm, we used the gradient descent method to learn the rule bases of a fuzzy algorithm. These rule bases are learned toward minimizing an objective function, which is called a performance cost function. The objective of fuzzy gain scheduler with intelligent learning algorithm is the generation of adequate gains, which minimize the error of system. The condition of every plant is generally changed as time gose. That is, the initial gains obtained through the analysis of system are no longer suitable for the changed plant. And we need to set new gains, which minimize the error stemmed from changing the condition of a plant. In this paper, we applied this strategy for reactor control of nuclear power plant (NPP), and the results were compared with those of a simple PI controller, which has fixed gains. As a result, it was shown that the proposed algorithm was superior to the simple PI controller.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.917-922
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• 2004

As the tasks of robots become more diverse, some complicated tasks have come to require force and position hybrid control. A compliant device can be used to control force and position simultaneously by separating the twist of the robot's end effector from the twist of compliance and freedom by using stiffness mapping of the compliant device. The development of a fuzzy gain scheduling scheme of control for a robot with a compliant device is described in this paper. Fuzzy rules and reasoning are performed on-line to determine the gain of twists based on wrench error and twist error and twist of compliance and twist of freedom ratio. Simulation results demonstrate that better control performance can be achieved in comparison with constant gain control.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.940-940
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• 2006

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.48.5-48
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• 2001

The resulting stabilizing controller in this paper consists of the disturbance estimator and the gain scheduled controller. The disturbance estimator tracks the unknown external disturbance and its derivative information in the closed-loop control system using fuzzy logic based adaptation law. Moreover, the gains of the stabilizing controller are appropriately scheduled according to the estimated values. Furthermore, since the estimation law is combined with the stabilizing controller in the closed control loop, it asymptotically minimizes the estimation error. In order to conrm the usefulness of the proposed control scheme, it is applied to the magnetic suspension systems.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2000.05a
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• pp.1-5
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• 2000

The conventional PID controller has been extensively used to speed control of marine diesel engines. However one of drawbacks is that its control performance can be degraded if the parameters are fixed on whole operating points. In this paper a scheme for integrating PID control and the fuzzy technique is presented to control speed of a marine diesel engine on whole operating points. At first the PID controller is designed at each speed mode whose parameters are optimally adjusted using a genetic algorithm, Then fuzzy "if-then" rules combine the controllers as a consequence part. To demonstrate the effectiveness of the proposed fuzzy controller a set of simulation works on a marine diesel engine are carried out.rried out.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.14-21
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• 2007

Sight Stabilization system is the control system to preserve Line of Sight for the targets though many nonlinear disturbances and vibrations are generated. In this paper, we identified Stabilization system using RLS algorithm, one of the system identification algorithm and found out the modeling of system. Considering nonlinear operational condition this paper proposes two Knowledge-base controllers - Fuzzy controller, Fuzzy PI Gain Scheduling controller, and simulates the performances of proposed controllers compare with Lead PI controller being used in Sight system of NFIV.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.449-454
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• 1994

This paper describes new PID control methods based on the fuzzy logic. PID gains are retuned after evaluating control performances of transient responses in terms of performance features. The retuning procedure is based on fuzzy rules and reasoning accumulated from the knowledge of experts on PID gain scheduling. For the case that the retuned PID gains result in worse CLDR (characteristics of load disturbance rejection) than the initial gains, an on-line tuning scheme of the set-point weighting parameter is, proposed. This is based on the fact that the set-point weighting method efficiently reduce either overshoot or undershoot without any degradation of CLDR. The set-point weighting parameter is adjusted at each sampling instant by the fuzzy rules and reasoning. As a result, better control performances were achived in comparison with die controllers tuned by the Z-N (Ziegler-Nichols) parameter tuning formula or by the fixed set-point weighting parameter.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.234-234
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• 2000

A direct torque control(DTC) based sensorless speed control system which employs a new closed loop flux observer is proposed. The flux observer takes an adaptive scheduling gains where motet speed is used as the scheduling variable. Adaptive nature comes from the fact that the estimated values of stator resistance and speed are included as observer parameters. The parameters of the PI controllers adopted in the adaptive law for the estimation of stator resistance and motor speed are determined by simple genetic algorithm. Simulation results in low speed region are given for comparison between proposed and conventional flux estimate scheme.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.114-116
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• 2004

The temperature profile control issue in the resistive welder for the electronic parts is discussed. The average current of the welder tip depends on the phase(on-time) of the AC power and the tip temperature maintains or increases/decreases depending on the integral of the current square and heat loss, The basic PID control algorithm with thermo-couple feedback is difficult to track the temperature profile for various parts and optimal gain changes much. So constant gain PID algorithm is not enough to cover various electronic parts welding and a Fuzzy-PID automatic gain tuning algorithm is devised and added to conventional PID algorithm and this hybrid control architecture is implemented and the experimental results are shown.

• Structural Engineering and Mechanics
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• v.41 no.3
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• pp.349-363
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• 2012

Fuzzy logic based control has recently been proposed for regulating the properties of magnetorheological (MR) dampers in an effort to reduce vibrations of structures subjected to seismic excitations. So far, most studies showing the effectiveness of these algorithms have focused on the use of a single MR damper. Because multiple dampers would be needed in practical applications, this study aims to evaluate the effects of multiple individually tuned fuzzy-controlled MR dampers in reducing responses of a multi-degree-of-freedom structure subjected to seismic motions. Two different fuzzy-control algorithms are considered, a traditional controller where all parameters are kept constant, and a gain-scheduling control strategy. Different damper placement configurations are also considered, as are different numbers of MR dampers. To determine the robustness of the fuzzy controllers developed to changes in ground excitation, the structure selected is subjected to different earthquake records. Responses analyzed include peak and root mean square displacements, accelerations, and interstory drifts. Results obtained with the fuzzy-based control schemes are compared to passive control strategies.