Structural modeling and control using neural networks

Jyh Ching Juang, Chi Yuan Chiang, Hussein M. Youssef

研究成果: Conference article同行評審


A context sensitive neural network is devised for structural system modeling and control. This neural networks attempts to blend existing structural modeling formulation into the neural network framework. One innovation of the neural network is to represent each structural vibration mode using a neuron. Thus, when the neural system converges, the modal data are identified. Another neural network paradigm that is identified for structural modeling is the adaptive vector quantization technique. It is shown that this learning scheme is able to resolve closely-spaced modes for large space structures. The context sensitive neural networks also allow the injection of robust control design in the context of neural network.

頁(從 - 到)1608-1618
期刊Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
出版狀態Published - 1994 十二月 1
事件Proceedings of the 35th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. Part 1 (of 5) - Hilton Head, SC, USA
持續時間: 1994 四月 181994 四月 20

All Science Journal Classification (ASJC) codes

  • 建築
  • 材料科學(全部)
  • 航空工程
  • 材料力學
  • 機械工業


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