• Title/Summary/Keyword: Recurrent fuzzy neural networks

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LMTT Positioning System Control using DR-FNN (DR-FNN을 이용한 LMTT Positioning System 제어)

  • Lee, Jin-Woo;Sohn, Dong-Sop;Min, Jung-Tak;Lee, Kwon-Soon
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2206-2208
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    • 2003
  • LMTT(Linear Motor-based Transfer Technology) is horizontal transfer system in the maritime container terminal for the port automation. The system is modeled PMLSM(Permanent Magnetic Linear Synchronous Motor) that is consists of stator modules on the rail and shuttle car(mover). Because of large variant of movers weight by loading and unloading containers, the difference of each characteristic of stator modules, and a stator module's default etc., LMCS(Linear Motor Conveyance System) is considered as that the system is changed its model suddenly and variously. In this paper, we will introduce the soft-computing method of a multi-step prediction control for LMCS using DR-FNN(Dynamically Constructed Recurrent Fuzzy Neural Network). The proposed control system is used two networks for multi-step prediction. Consequently, the system has an ability to adapt for external disturbance, cogging force, force ripple, and sudden changes of itself.

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