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Control of a cantilever pipe conveying fluid using neural network

机译:利用神经网络控制悬臂输送流体

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The purpose of this paper is to investigate the dynamic behavior of a fluid conveying pipe and to propose suitable control strategies in order to eliminate or suppress its vibration. The system under consideration consists of a uniform, straight, vertical cantilever pipe which conveys incompressible fluid. Governing equation of motion for free transverse vibration is derived by using Newtonian approach. This equation is dis-cretized using the finite element method. The effects of the fluid flow speed on open loop response of the system are investigated. The results show unstable behavior when the flow velocity exceeds a critical value. Neural network based controller are applied to the system to suppress the pipe vibration and to improve the stability conditions. The results show that neural network based controller successfully suppresses the vibration when the critical flow velocity is exceeded. Moreover, it holds the system response in the stable region at higher flow velocities. NN based controller learns the variation of the system against unknown flow velocities in the system and adapts itself against unknown changes.
机译:本文的目的是研究流体输送管的动态行为,并提出适当的控制策略以消除或抑制其振动。所考虑的系统由均匀,笔直,垂直的悬臂管组成,该管用于输送不可压缩的流体。利用牛顿法推导了自由横向振动的运动控制方程。该方程使用有限元方法离散化。研究了流体流速对系统开环响应的影响。结果表明,当流速超过临界值时,行为不稳定。基于神经网络的控制器被应用到系统中,以抑制管道振动并改善稳定性条件。结果表明,当超过临界流速时,基于神经网络的控制器成功地抑制了振动。而且,它在较高流速下将系统响应保持在稳定区域中。基于NN的控制器可根据系统中未知的流速来学习系统的变化,并使其适应未知的变化。

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