• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.1
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• pp.60-68
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• 1999

This paper deals with the tracking control problem of industrial robotic manipulators with unknown or changing dynamics. The proposed method makes use of multiple moodels and switching mechanism by fuzzy inference of the manipulator in an indirect adaptive controller architecture. The models used for the indmtification of the manipliator are identical, except for the initial estimates of the unknown inertial pararmeters of the manipulator and its load. The torque input that is applied to the joint actuators is determined at every instant by the identification model that best approximates the robot dynamics. Simulation results are also included to dermnstrate the improvement in the tracking perfermance when the proposed method is used.s used.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.6
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• pp.84-90
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• 2004

Many control techniques have been proposed in order to improve the control performance in the control system. In the feedback control system the output of controller is generally used as the input of a plant But the undesired noise is included in the output of a controller. Therefore, there is a need to use a precompensator for rejecting the undesired noise and improving the response characteristic of a system. In this paper, the design method of a precompensator is proposed for the model following control in the I-PD control system. The proposed precompensator is implemented with a neural network. The games of a precompensator are adjusted automatically to obtain a desired response of a system when the response characteristic of a system is changed under a condition.

• Journal of Drive and Control
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• v.16 no.2
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• pp.22-29
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• 2019

This study presented a model predictive tracking control algorithm of autonomous truck based on object state estimation using extended Kalman filter. To design the model, the 1-layer laser scanner was used to estimate position and velocity of the object using extended Kalman filter. Based on these estimations, the desired linear path for object tracking was computed. The lateral and yaw angle errors were computed using the computed linear path and relative positions of the truck. The computed errors were used in the model predictive control algorithm to compute the optimal steering angle for object tracking. The performance evaluation was conducted on Matlab/Simulink environments using planar truck model and actual point data obtained from laser scanner. The evaluation results showed that the tracking control algorithm developed in this study can track the object reasonably based on the model predictive control algorithm based on the estimated states.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.867-872
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• 2022

The effect of load is an important factor in precise speed control of a motor. n this study, we design a state observer that can estimate and define one state of disturbance including errors and nonlinear terms of mathematical models, which is not easy with a mathematical model. Then, the observation gain is set so that the estimation error of the state observation converges to 0, and the estimated state is used in the back stepping controller to design a controller capable of precise speed tracking. As a result of applying to 1 [hw] class Interior Permanent Magnet Synchronous Motor, excellent stste variable observation and tracking performance can be confirmed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.472-477
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• 2023

In this paper, we proposes the use of Model Predictive Control (MPC) techniques to enable quadcopter drones to effectively follow paths and maintain flight safety even under dynamic external environments and disturbances. Through simulations conducted in MATLAB/Simulink, the performance of two controllers, PID and MPC, is compared in flight scenarios with disturbances. The proposed design method shows that the MPC controller, when compared to the PID controller, exhibits a difference in the Mean Squared Error between the intended flight path and the actual path of the quadcopter drone. This difference is 0.2 in performance under no disturbance, and it increases to 0.8 under disturbance, demonstrating the improved path following accuracy of the MPC controller.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.2
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• pp.139-145
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• 2014

Periodic disturbance compensators are widely used in track following servo systems. They are commonly designed and implemented by adaptive feedforward compensators or internal model based compensators. In track following servo systems, the gains of the compensators should be determined considering the change of the sensitivity transfer function and the implementation methods should be selected considering the system environment. This paper proposes a guide for determining gains of the periodic disturbance compensators. Various simulation and experimental results are presented to see the effect of gains. In addition, this paper introduces the various types of implementation methods and compares their merits and demerits.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.121-128
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• 2000

In this paper, the control algorithm fur an autonomous vehicle is studied and applied to an actual 2 wheel-driven vehicle system. In order to control a nonholonomic system, the kinematic model for an autonomous vehicle is constructed by relative velocity relationship about the virtual point at distance from the vehicle's frame. And the optimal controller that based on the kinematic model is operated on purpose to track a reference vehicle's path. The actual system is designed with named 'HYAVI' and the system controller is applied. Because all the results of simulation don't satisfy the driving conditions of HYAVI, a reformed control algorithm that satisfies an actual autonomous vehicle is applied at HYAVI. At the results of actual experiments, the path tracking works very well by the reformed control algorithm. An autonomous vehicle that applied this control algorithm can be easily used for a path generation algorithm.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1755-1756
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• 2006

본 논문에서는 하이브리드 발전 시스템에서의 최대 전력 추종을 위한 디지털 퍼지 제어기 설계를 목표로 한다. 하이브리드 발전 시스템은 풍력과 태양광, 두 개의 발전 시스템으로 구성된다. 각 발전기에서 전압과 전류는 일반적으로 비선형 관계에 있기 때문에, 퍼지 모델 기반 제어기를 사용하여 비선형성을 효율적으로 제어하게 된다. 그리고 마이크로프로세서 기반 제어 시스템의 구축을 위하여 최신 디지털 재설계 기법을 사용, 디지털 퍼지 제어기를 설계하게 된다. 마지막으로 제안된 플랜트를 통한 실험으로써 본 논문의 우수성을 입증하고자 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.476-480
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• 2012

In this paper, artificial potential field(APF) is applied to formation control for the leader-following swarm robot. Furthermore, APF is constructed by applying the electrical field model. Moreover, to model the obstacle effectively, each obstacle has different form due to the electrical field equation. The proposed method is formed as two sub-objective: path planning for the leader-robot and following-robots following the leader-robot. Finally, simulation example is given to prove the validity of proposed method.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.170-175
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• 1999

본 논문에서는 국내에서 운전 중인 한 가스터빈 출력제어 회로의 구성을 살펴보고 현장에서 취득한 자료를 근거로 하여 가스터빈의 모델과 제어기의 조정, 그리고 MW 신호 피이드백 회로에 필터의 사용효과를 시뮬레이션을 통해 살펴보았다. 전력계통의 주파수가 가스터빈 출력제어계의 시상수에 비해 상당히 빠르게 변하므로 자동 주파수 추종을 할 경우 제어계가 쉽게 불안정해진다. 이 출력제어계의 MW 피이드백 회로의 1차지연 요소를 사용하면 안정성 향상에 좋은 효과가 있으며, 이 지연요소의 시상수를 크게 할수록 안정도는 더 향상되며 Open Loop의 특성을 보이게 된다. 그러나, 주파수 추종운전이 아닌 운전원의 출력 증감발 요구에는 시간지연 없이 응답을 하여야 하므로 적절한 설정을 할 필요가 있다. 가스터빈의 연료제어 계통을 포함한 출력제어계에 순수 시간지연 요소가 없으면 피이드백 회로에 1차지연 요소를 사용하지 않는 것이 더 좋은 출력제어 응답을 나타낸다. 그러나 실제 모들 가스터빈에는 다소 시간지연 요소를 포함하고 있으므로 일반적으로 피이드백 회로에 시간지연 요소를 사용하므로써 안정성을 향상시킬 수 있다.