• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.93.2-93
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• 2001

This paper presents the implementation of fuzzy PI gain scheduling controller (FPICGS) for controlling flexible joint robot arms with uncertainties from time-varying load. The term FPICGS is called based on a combination of fuzzy PI control scheme with a set of rule bases. Principle of design for a FPICGS is given along with the implementation of the designed computer aided control system. The experiment reveals an effectiveness of the proposed control scheme for flexible joint robot arms driven by a DC motorhooked with a spring which both parameters are completely unknown parameters ...

• 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.

• 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.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.4
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• pp.435-440
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• 2000

The speed control system of diesel engine is considerably nonlinear. Therefore, a countermeasure such as gain scheduling used to be incorporated to compensate this nonlinearity. On the other hand, it is said that fuzzy control is very robust against nonlinearity. But it is difficult to get a satisfactory response with only fuzzy control in real system. In this paper authors design a fuzzy-PI controller for the speed control of Medium diesel engine and carry out experiments with dedicate system implemented by Intel 80916KC to real diesel engine, Deawoo MAN 6Cyl., 1800rpm driving 3$\psi$220V, 150KW generator. We confirm the effectiveness of proposed control system.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.156-160
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• 1997

In this paper, the control scheme is proposed that PI controller parameter used for TAH speed control is adapted by fuzzy logic method using only the motor current waveform. By scheduling PI parameters, minimization of the vibration and the energy consumption and overcoming AoP loads becomes possible. In in vitro tests experimental results show our approach is a good scheme that is adapted to changing afterloads well.

• 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.