• KIEE International Transactions on Power Engineering
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• v.3A no.4
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• pp.181-190
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• 2003

This paper presents the design of a fuzzy power system stabilizer (FPSS) using an adaptive evolutionary algorithm (AEA). AEA consists of genetic algorithm (GA) for a global search capability and evolution strategy (ES) for a local search in an adaptive manner when the present generation evolves into the next generation. AEA is used to optimize the membership functions and scaling factors of the FPSS. To evaluate the usefulness of the FPSS, we applied it to a single-machine infinite bus system (SIBS) and a power system simulator at the Korea Electrotechnology Research Institute. The FPSS displays better control performance than the conventional power system stabilizer (CPSS) for a three-phase fault in heavy load, which is used when tuning FPSS. To show the robustness of the FPSS, it is applied with disturbances such as change of mechanical torque and three-phase fault in nominal and heavy load, etc. The FPSS also demonstrates better robustness than the CPSS. Experimental results indicate that the FPSS has good system damping under various disturbances such as one-line to ground faults, line parameter changes, transformer tap changes, etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9C
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• pp.922-928
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• 2007

This paper presents the fast adaptive algorithm which applies an approximation scheme into RLS algorithm. The proposed algorithm(D-RLS) derives a QRD RLS algorithm derivation process from RLS algorithm recursively. D-RLS has the similar pattern as the algorithm having the approximation that input signals are separated respectively. Computational complexity of D-RLS is O(N), fewer than $O(N^2)$. To evaluate performance of proposed algorithm, we use the system identification method of FIR and Volterra system. And, finally, we can show D-RLS has an excellent performance.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.862-864
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• 1999

Adaptive Fuzzy control system is very powerful in nonlinear system, but That system require exactly membership function and parameter. If the membership function and parameter are not exact, the system will generate chattering. Using the Pole assignment compensator can remove the chattering and steepest descent method can reduce the convergence time. In this Paper, this algorithm applicate to the Inverted pendulum, so save proof of algorithm that is to be vigorous.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.93-95
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• 2006

In many control system applications, the system designed must not only satisfy the damping and accuracy specifications, but the control must also yield performance that is robust to external disturbance and parameter variations. We have shown that feedback in conventional control systems has the inherent ability of reducing the effects of external disturbance and parameter variations. Unfortunately, robustness with the conventional feedback configuration is achieved only with a high loop gain, which is normally detrimental to stability. The design of intelligent, autonomous machines to perform tasks that are dull, repetitive, hazardous, or that require skill, strength, or dexterity beyond the capability of humans is the ultimate goal of robotics research. This paper prove the robust control using Analog Adaptive Resonance Theorv(ART2) Algorithm about case study.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1680-1681
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• 2007

This paper deals with RLS algorithm using Newton-Raphson method based adaptive forgetting factor for a passive telemetry RF sensor system in order to estimate the time variant parameter to be included in RF sensor model.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.232-236
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• 2000

In this paper a novel estimation algorithm of mechanical parameters in two-mass system is proposed. The inertia of a load and a motor and the stiffness are estimated by using RLS (Recursive Least Square) algorithm and acceleration information of motor. The effectiveness of the proposed scheme is verified with simulation and experiments results.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2088-2090
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• 1997

This paper consists of the speed sensorless vector control of induction motors with the estimation of rotor resistance. In the application of variable-speed induction motor drives, if an inaccurate rotor resistance is used because the rotor resistance can change due to skin effects and temperature variables, it is difficult to achieve a collect field orientation. In this paper, to overcome these difficulties adaptive algorithm is designed for rotor resistance identification. The proposed adaptive algorithm for rotor resistance estimation in the synchronous reference frame is applied by sliding mode current controller satisfing persistent excitation(PE) condition. Adaptive flux observer is here used for the purpose of estimating rotor flux and speed in the speed sensorless scheme. Computer simulations are carried out to verify the validity of the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.8
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• pp.914-921
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• 1992

In this paper, we introduce a Walsh network and an LMS algorithm, and show how these can be realized as an adaptive equalizer. The Walsh network is built from a set of Walsh and Block pulse functions. In the LMS algorithm, the convergence factor is an important design parameter because it governs stability and convergence speed, which depend on the proper choice of the convergence facotr. The conventional adaptation techniques use a fixed time constant convergence factor by the method of trial and error. In this paper, we propose an optimal method in the choice of the convergence factor. The proposed algorithm depends on the received signal and the output of the Walsh network in real time.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.636-639
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• 1997

In this paper, a dynamic control scheme is proposed which not only compensates for the lateral dynamics and longitudinal dynamics but also deal with the yaw motion dynamics. Using the dynamic control technique, adaptive and learning algorithm together, the proposed controller is not only robust to disturbance and parameter uncertainties but also can learn the inverse dynamics model in steady state. Based on the proposed dynamic control scheme, a dynamic vehicle simulator is contructed to design and test various control techniques for 4-wheel steering vehicles.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.15-18
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• 2003

This paper presents an adaptive control scheme for parking or regulating a nonholonomic mobile robot of an unicycle type with parameter uncertainty. The kinematics can be described with Brockett's nonholonomic integrator. The control law is designed in cylindrical coordinates together with the estimation law for the uncertain parameters such that the controlled signals converge to zero while guaranteeing the boundedness of the estimation errors. The effectiveness of the proposed scheme is demonstrated using simulations.