• Title/Summary/Keyword: NN self-tuner

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An Automatic Travel Control of a Container Crane using Neural Network Predictive PID Control Technique

  • Suh Jin-Ho;Lee Jin-Woo;Lee Young-Jin;Lee Kwon-Soon
    • International Journal of Precision Engineering and Manufacturing
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    • v.7 no.1
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    • pp.35-41
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    • 2006
  • In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2-DOF PID controller. The experimental results jar an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard.

An Automatic Travel Control of a Container Crane using Neural Network Predictive PID Control Technique (신경회로망 예측 PID 제어법을 이용한 컨테이너 크레인의 자동주행제어)

  • Suh Jin Ho;Lee Jin Woo;Lee Young Jin;Lee Kwon Soon
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.1
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    • pp.61-72
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    • 2005
  • In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2 DOF PID controller. The experimental results for an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard. Accordingly, the proposed algorithm in this study can be readily used for industrial applications

A Study on Development ATCS of Transfer Crane using Neural Network Predictive Control (신경회로망 예측제어에 의한 Transfer Crane의 ATCS개발에 관한 연구)

  • Sohn, Dong-Seop;Lee, Jin-Woo;Lee, Young-Jin;Lee, Kwon-Soon
    • Journal of Navigation and Port Research
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    • v.26 no.5
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    • pp.537-542
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    • 2002
  • Recently, an automatic crane control system is required with high speed and rapid transportation. Therefore, when container is transferred from th intial coordinate to the finial coordinate, the container paths should be built in terms of the least time and no swing. So in this paper, we calculated the anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the neural network predictive PID (NNPPID) controller to control the precise navigation. The proposed predictive control system is composed of the neural network predictor, PID controller, neural network self-tuner which yields parameters of PID. Analyzed crane system through simulation, and proved excellency of control performance than other conventional controllers.