• 제목/요약/키워드: Optimal driving control algorithm

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Development of Wired Monitoring System for Layers Rearing in Muti-tier Layers Battery by Machine Vision (기계시각을 이용한 고단 직립식 산란계 케이지의 유선 감시시스템 개발)

  • Zheng, S.Y.;Chang, D.I.;Lee, S.J.;So, J.K.
    • Journal of Biosystems Engineering
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    • v.31 no.5 s.118
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    • pp.436-442
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    • 2006
  • This research was conducted to design and develop a wired monitoring system for judging if sick or dead layers (SDL) exist in multi-tier layers battery (MLB) by machine vision, and to analyze its performance. In this study, 20 Brown Leghorn (Hi-Brown) layers aged 37 weeks old, were used as the experimental animals. The intensity of concern paid by layers on feed was over 90% during 5 minutes and 30 seconds after providing feed, and normal layers (NL) had been standing to take feed for that period. Therefore, in this study, the optimal judging time was set by this test result. The wired monitoring system developed was consisted of a driving device for carrying machine vision systems, a control program, a RS232 to RS485 convertor, an automatic positioning system, and an image capture system. An image processing algorithm was developed to find SDL in MLB by the processes of binary processing, erosion, expansion, labeling, and reckoning central coordinate of the captured images. The optimal velocity for driving unit was set up as 0.13 m/s by the test results for wired monitoring system, and the proximity switch was controlled not to be operated for 1.0 second after first image captured. The wired monitoring system developed was tested to evaluate the remote monitoring performance at lab-scale laying hen house. Results showed that its judgement success.ate on normal cage (without SDL) was 87% and that on abnormal cage (with SDL) was 90%, respectively. Therefore, it would be concluded that the wired monitoring system developed in this study was well suited to the purpose of this study.

A Study for Application of Active Magnetic Bearing using Quantitative Feedback Theory (Quantitative Feedback Theory를 이용한 능동 자기베어링의 적용 연구)

  • Lee, Gwan-Yeol;Lee, Hyeong-Bok;Kim, Yeong-Bae
    • Journal of the Korean Society for Precision Engineering
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    • v.18 no.11
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    • pp.107-115
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    • 2001
  • Most of rotating machineries supported by contact bearing accompany lowering efficiency, vibration and wear. Moreover, because of vibration, which is occurred in rotating shaft, they have the limits of driving speed and precision. The rotor system has parametric variations or external disturbances such as mass unbalance variations in long operation. Therefore, it is necessary to research about magnetic bearing, which is able to support the shaft without mechanical contact and to control rotor vibration without being affected by external disturbances or parametric changes. Magnetic bearing system in the paper is composed of position sensor, digital controller, actuating amplifier and electromagnet. This paper applied the robust control method using quantitative feedback theory (QFT) to control the magnetic bearing. It also proposed design skill of optimal controller, in case the system has structured uncertainty, unstructured uncertainty and disturbance. Reduction of vibration is verified at critical rotating speed even external disturbance exists. Unbalance response, a serious problem in rotating machinery, is improved by magnetic bearing using QFT algorithm.

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Multiple Path-planning of Unmanned Autonomous Forklift using Modified Genetic Algorithm and Fuzzy Inference system (수정된 유전자 알고리즘과 퍼지 추론 시스템을 이용한 무인 자율주행 이송장치의 다중경로계획)

  • Kim, Jung-Min;Heo, Jung-Min;Kim, Sung-Shin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.8
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    • pp.1483-1490
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    • 2009
  • This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

Design of the control Algorithm for Improvement of the Convenience the Active-type Walking Aid (전동 보행보조기의 편의성 향상을 위한 제어기 설계)

  • Lee, D.K.;Kong, J.S.;Goh, M.S.;Kang, S.J.;Lee, S.M.;Lee, E.H.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.5 no.1
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    • pp.17-25
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    • 2011
  • This paper aims to find the optimal control gain for enhancing the convenience of electric walking frames and design a control algorithm. With the recent advances in medical technology, there has been a rapid increase in the aging population and a variety of mobile walking frames have been developed for improvement of the quality of life. However, the manual walking frames of such mobile aids don't have any electric motor which helps facilitate elderly users' walking and thus are not efficient enough for the old people of weak strength to use especially when moving on uneven surfaces such as slopes or thresholds. The types of electric walking frames have been developed to overcome such inefficiency. Electric walking frames require users' control operations for motor driving unlike manual frames. Therefore, when they are not properly handled, it causes considerable inconvenience to their users. The present study compared the electric walking frames with manual ones in terms of operational convenience and attempted to improve the user convenience of walking frames varying the control value for user convenience based on certain standards. This paper presented a haptic sensor designed to recognize the will to walk and measure the degree of convenience and proposed a control algorithm for improvement of convenience. For user convenience, this paper evaluated the relative convenience of walking frames in view of changing differences between the center of vehicle (COV) and the center of position (COP). With the employment of an electric walking frame and a new measuring method, all the processes were experimentally tested and validated.

Study on the Failure Diagnosis of Robot Joints Using Machine Learning (기계학습을 이용한 로봇 관절부 고장진단에 대한 연구)

  • Mi Jin Kim;Kyo Mun Ku;Jae Hong Shim;Hyo Young Kim;Kihyun Kim
    • Journal of the Semiconductor & Display Technology
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    • v.22 no.4
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    • pp.113-118
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    • 2023
  • Maintenance of semiconductor equipment processes is crucial for the continuous growth of the semiconductor market. The process must always be upheld in optimal condition to ensure a smooth supply of numerous parts. Additionally, it is imperative to monitor the status of the robots that play a central role in the process. Just as many senses of organs judge a person's body condition, robots also have numerous sensors that play a role, and like human joints, they can detect the condition first in the joints, which are the driving parts of the robot. Therefore, a normal state test bed and an abnormal state test bed using an aging reducer were constructed by simulating the joint, which is the driving part of the robot. Various sensors such as vibration, torque, encoder, and temperature were attached to accurately diagnose the robot's failure, and the test bed was built with an integrated system to collect and control data simultaneously in real-time. After configuring the user screen and building a database based on the collected data, the characteristic values of normal and abnormal data were analyzed, and machine learning was performed using the KNN (K-Nearest Neighbors) machine learning algorithm. This approach yielded an impressive 94% accuracy in failure diagnosis, underscoring the reliability of both the test bed and the data it produced.

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Design of lift-down kitchen cabinet for elderly and disabled (고령자 및 장애인을 위한 승강형 주방 상부장 설계)

  • Kibum Shim;Hoon Shim;Geon-Hyeok Lim;Jiwon Jang;Sang-Hyun Kim
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.465-470
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    • 2024
  • Kitchen cabinets are widely used for their spacious storage and efficient use of space, but their high installed location makes it difficult for the elderly and disabled to access. Therefore, in this paper, we propose a new height-adjustable kitchen cabinet that can be used more easily and safely. The lift-down range of cabinet was set considering the installation location of cabinet for efficient use of kitchen space and the maximum height accessible to the elderly and disabled, and the link geometry and driving method of the complex link mechanism were determined through the mechanism design procedure to ensure that the selected floor come down safely along the optimal descend path. In addition, the appropriate motor and control algorithm were added to allow the user to descend to the desired height with a simple button operation. It was confirmed through actual production that the proposed linkage mechanism performs the desired lift-down motion.