• Title/Summary/Keyword: PI-Fuzzy Controller

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A Study on the Automation Equipment Development of RC Technology(II) -Improvement of Position Controller- (RC 기술의 자동화 장치 개발에 관한 연구(II) -위치 제어기의 개선-)

  • Kim, Ki-Joon;Kim, Sang-Jin;Song, Ja-Youn
    • Proceedings of the KIEE Conference
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    • 1994.11a
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    • pp.314-316
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    • 1994
  • The operation of RC(Rod Consolidation) technology carry out highly radiation environment. It requires remote operation and automation for efficient handling and for minimizing radiation exposure to the operator. So we investigated up and down position control of shock absorber device in RC system. To verify the research experimentally, a RC system was set up and PI control method was applied. Fuzzy control method was also tested to further improve control behavior.

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Study on a Navigated Simulator of the Underwater Cleaning Robot (수중청소로봇의 운항 제어용 시뮬레이터 연구)

  • Choi, Hyeung-Sik;Kang, Jin-Il;Hong, Sung-Yul;Park, Han-Il;Seo, Joo-No;Kim, Moon-Hwan;Gwon, Kyeong-Yeop
    • Journal of Navigation and Port Research
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    • v.33 no.6
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    • pp.387-393
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    • 2009
  • In this paper, a 3-D simulator was developed to estimate visually the performance of propelling and integrated control system of the underwater cleaning robot. Based on the dynamics analysis of the UCR, the 3-D model of the UCR was used in the simulator in which position and velocity are included Also, an input and control system using a joystick was developed, and the simulator was applied to the input and control of the simulator. Moreover, an integrated navigation control system was designed, and its performance was validated by a way-point simulator including a PI-based fuzzy control law.

Robust Real-time Control of Autonomous Mobile Robot Based on Ultrasonic and Infrared sensors (초음파 및 적외선 센서 기반 자율 이동 로봇의 견실한 실시간 제어)

  • Nguyen, Van-Quyet;Han, Sung-Hyun
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.1
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    • pp.145-155
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    • 2010
  • This paper presents a new approach to obstacle avoidance for mobile robot in unknown or partially unknown environments. The method combines two navigation subsystems: low level and high level. The low level subsystem takes part in the control of linear, angular velocities using a multivariable PI controller, and the nonlinear position control. The high level subsystem uses ultrasonic and IR sensors to detect the unknown obstacle include static and dynamic obstacle. This approach provides both obstacle avoidance and target-following behaviors and uses only the local information for decision making for the next action. Also, we propose a new algorithm for the identification and solution of the local minima situation during the robot's traversal using the set of fuzzy rules. The system has been successfully demonstrated by simulations and experiments.