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Fuzzy neural network multi-modal vibration control of thin cylindrical shells laminated with photostrictive actuators

机译:光致伸缩致动器薄层圆柱壳的模糊神经网络多模态振动控制

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摘要

In this paper, the multi-modal vibration control of a simply supported thin cylindrical shell laminated with photostrictive actuators is studied. First, the photo-electric/shell coupling equations of a cylindrical shell laminated with the multi-layer actuator configuration are presented. Moreover, in view of the nonlinear and time-variant characteristics of photostrictive actuators, a fuzzy neural network (FNN) controller with adaptive learning rates is developed to attenuate multi-mode vibration of photo-electric laminated thin cylindrical shells. This approach has learning ability for responding to the time-varying characteristic of the multi-mode vibration induced by disturbance. Its control rule bank can be established and modified continuously by on-line learning. Finally, numerical simulation results are provided to show that the proposed intelligent controller could effectively suppress multi-mode vibration of photo-electric laminated thin cylindrical shells.
机译:本文研究了带有光致伸缩致动器的简单支撑薄圆柱壳的多模式振动控制。首先,提出了具有多层致动器构造的圆柱壳的光电/壳耦合方程。此外,鉴于光致伸缩致动器的非线性和时变特性,开发了具有自适应学习率的模糊神经网络(FNN)控制器,以衰减光电层压薄圆柱壳的多模振动。这种方法具有学习能力,可以响应扰动引起的多模振动的时变特性。它的控制规则库可以通过在线学习不断建立和修改。最后,数值仿真结果表明,所提出的智能控制器能够有效地抑制光电层压薄圆柱壳的多模振动。

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