• Title, Summary, Keyword: Zero Position Adjustment

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PI Controller Design Based on Characteristic Parameters and Zero Position Adjustment for an Oil Cooler System (오일쿨러시스템의 특성근과 영점 조절에 의한 고성능 PI 제어기 설계)

  • Choi, Do-Kyung;Jeong, Seok-Kwon
    • Journal of Power System Engineering
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    • v.20 no.4
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    • pp.83-90
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    • 2016
  • This study proposes a high-performance PI controller design method for an oil cooler system in conjunction with zero position adjustment and the characteristic parameters in its closed loop control system. The characteristic parameters included PI gains are decided by design specifications such as settling time and overshoot. The fine tuning on decided gains was performed by adjustment the zero position to get more desirable control performances. The simulations and experimental results show that the proposed PI controller design for an oil cooler system was possible to accomplish good control performances and to satisfy the design specifications.

A Study on the Stabilization Force Control of Robot Manipulator

  • Hwang, Yeong Yeun
    • International Journal of Safety
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    • v.1 no.1
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    • pp.1-6
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    • 2002
  • It is important to control the high accurate position and force to prevent unexpected accidents by a robot manipulator. Direct-drive robots are suitable to the position and force control with high accuracy, but it is difficult to design a controller because of the system's nonlinearity and link-interactions. This paper is concerned with the study of the stabilization force control of direct-drive robots. The proposed algorithm is consists of the feedback controllers and the neural networks. After the completion of learning, the outputs of feedback controllers are nearly equal to zero, and the neural networks play an important role in the control system. Therefore, the optimum adjustment of control parameters is unnecessary. In other words, the proposed algorithm does not need any knowledge of the controlled system in advance. The effectiveness of the proposed algorithm is demonstrated by the experiment on the force control of a parallelogram link-type robot.

A Study on the Force Control of a Robot Manipulator Using Neural Networks (신경회로망을 이용한 로봇 매니퓰레이터의 힘 제어에 관한 연구)

  • 황용연
    • Journal of Advanced Marine Engineering and Technology
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    • v.21 no.4
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    • pp.404-413
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    • 1997
  • Direct-drive robots are suitable to position and force control with high accuracy, but it is difficult to design a controller which gives satisfactory perfonnance because of the system's nonlinearity and link-interactions. This paper is concerned with the force control of direct-drive robots. The pro¬posed algorithm consists of feedback controllers and a neural network. Mter the completion of learning, the outputs of feedback controllers are nearly equal to zero, and the neural network con¬troller plays an important role in the control system. Therefore, the optimum adjustment of parameters of feedback controllers is unnecessary. In other words, the proposed algorithm does not need any knowledge of the controlled system in advance. The effectiveness of the proposed algo¬rithm is demonstrated by the experiment on the force control of a parallelogram link-type direct¬drive robot.

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