• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.167-168
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• 2006

This paper is concerned about the development system that the bead width's size can be controlled. In order to control the bead width, DC motor driving slide on auto carriage is used. The adjustment of bead width is carried by amplitude and weaving shape is controlled by MCU(Micro Controller Unit). We confirmed the result by tracking experiments.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.144-147
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• 2000

Controller refinement scheme to improve the performance of a conventional system automatically in frequency domain is proposed. The controller automatic tuning method features using experimental frequency responses of the conventional closed-loop system the conventional controller, and the improved closed-loop system, instead of poorly modeled plant due to non-linearities and disturbances. The improved closed-loop system characteristics is automatically acquired by the conventional closed-loop system characteristics and the proposed performance index in system bandwidth. And the proper controller is realized by least squares approximation in frequency domain. To testify the usefulness of the approach, the path tracking control of robot arm is performed. Experimental results and analytic results are well-matched.

• 유공압시스템학회:학술대회논문집
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• 2010.06a
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• pp.62-65
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• 2010

Field robot represented by excavator can be applied for various working in manufacturing, construction, agriculture etc. Because of the flexibility of its multi-joint mechanism and the high power of hydraulic actuators. Since the excavator operates in the hazardous working circumstance, operators exposed in harmful environment. Therefore, automation system has been investigated to protect from the harmful environment. In this paper, the method to construct the remote control system is proposed. The remote control system is consisted of a manual and auto mode. Manual mode controls a hydraulic cylinder as open loop control. and auto mode controls the end effecter of excavator using tracking control system. The efficiency of remote control system was evaluated through the field test.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1034-1036
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• 1996

In this paper, an adaptive fuzzy logic controller is presented for auto-tunning of the scaling factors by using learning capability of neural networks. The proposed scheme consists of the FLC which includes the PI-type FLC and PD-type FLC in parallel form and the neural network which learns scale factors of FLC. Computer simulations were performed to illustrate the effectiveness of a proposed scheme. A proposed FLC controller was applied to the second order system and velocity control of the brushless DC motors. For the design of the FLC, tracking error, change of error, and acceleration error are selected as input variables of the FLC and three seal e factors were used in the parallel-type FLC. This scheme can be used to reduce the difficulty in the selection of the scale factors.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.438-444
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• 1997

Recently, optical disk drives are increasingly demanded to have higher speed as well as high information density, especially for applications like CD-ROM drives. To this end, improvement of their optical pick-up structure and control is recognized the very challenging issue. In this paper, the 2-D motion of the pick-up is first analytically modelled to identify the cause and effect of the troublesome cross coupling between auto-focusing and tracking directions. Subsequently, the overall system equations are derived to include the dynamics of the related components in the auto-focusing servo system. While its unmeasurable parameters being estimated by the least square error method, a simple but decent linear model can be obtained within its operating frequency range. To design the high speed and robust positional servo controller, the design specifications are detailed and H$\sub$.inf./ control method is employed based on the simple model. Using the pickup in a commercial 8 fold speed CD-ROM drive as an example, performance of the designed controller is verified by realtime experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.77.5-77
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• 2001

A Robot vision system with a visual skill so as take information for arbitrary target or object has been applied to auto-inspection and assembling system. It catches the moving target with the manipulator by using the information from the vision system. The robot needs some information where the moving object will place after certain time. A camera is fixed on a robot manipulator, not on the fixed support outside of the robot. It secures wider working area than the fixed camera, and it dedicates to auto scanning of the object. It computes some information on the object center, angle and speed by vision data, and can guess grabbing spot by arriving time. When the location ...

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.123-128
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• 2021

This paper present box feature estimation from LiDAR point cluster using maximum likelihood Method. Previous LiDAR tracking method for autonomous driving shows high accuracy about velocity and heading of point cluster. However, Assuming the average position of a point cluster as the vehicle position has a lower accuracy than ground truth. Therefore, the box feature estimation algorithm to improve position accuracy of autonomous driving perception consists of two procedures. Firstly, proposed algorithm calculates vehicle candidate position based on relative position of point cluster. Secondly, to reflect the features of the point cluster in estimation, the likelihood of the particle scattered around the candidate position is used. The proposed estimation method has been implemented in robot operating system (ROS) environment, and investigated via simulation and actual vehicle test. The test result show that proposed cluster position estimation enhances perception and path planning performance in autonomous driving.

• Journal of Auto-vehicle Safety Association
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• v.15 no.3
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• pp.17-26
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• 2023

This paper presents extended state feedback control based on impulse response for lane change of autonomous driving vehicle. The triple characteristic root of path tracking system and longitudinal velocity determine feedback gains. We suggest a resemblance of impulse response curve of the system and lane change trajectory of the vehicle. The root affects the duration of lane change and lateral acceleration. The effect of limited lateral acceleration and saturation of steering angle will be analyzed and discussed. Finally, simulation results will show the trajectory of lane change based on impulse response under limitation of lateral acceleration.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.149-156
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• 2019

In the field of maintenance of power transmission lines, drones have been used for their patrol and inspection by KEPCO since 2017. This drone technology was originally developed by KEPCO Research Institute, and now workers from four regional offices of KEPCO have directly applied this technology to the drone patrol and inspection tasks. In the drone inspection system, a drone with an optical zooming camera and a thermal camera can fly automatically along the transmission lines by the ground control system developed by KEPCO Research Institute, but its camera gimbal has been remotely controlled by a field worker. Especially the drone patrol and inspection has been mainly applied for the transmission lines in the inaccessible areas such as regions with river-crossings, sea-crossings and mountains. There are often communication disruptions between the drone and its remote controller in such extreme fields of mountain areas with many barriers. This problem may cause the camera gimbal be out of control, even though the inspection drone flies along the flight path well. In addition, interference with the reception of real-time transmitted videos makes the field worker unable to operate it. To solve these problems, we have developed the auto-tracking camera gimbal system with deep learning method. The camera gimbal can track the transmission line automatically, even when the transmitted video on a remote controller is intermittently unavailable. To show the effectiveness of our camera gimbal system, its field test results will be presented in this paper.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.1
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• pp.79-86
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• 2012

This paper proposes PID and RIC (Robust Internal-loop Compensator) based motion controller using dual learning algorithm for position control of linear synchronous motor respectively. Its gains are auto-tuned by using two learning algorithms, reinforcement learning and neural network. The feedback controller gains are tuned by reinforcement learning, and then the feedforward controller gains are tuned by neural network. Experiments prove the validity of dual learning algorithm. The RIC controller has better performance than does the PID-feedforward controller in reducing tracking error and disturbance rejection. Neural network shows its ability to decrease tracking error and to reject disturbance in the stop range of the target position and home.