Direct inverse control for active vibration suppression using artificial neural networks
Direct inverse control for active vibration suppression using artificial neural networks
复制标题
使用人工神经网络进行主动振动抑制的直接逆控制
DOI：
10.1177/1077546320924253
复制
发表时间：
2020
影响因子：
2.8
通讯作者：
A. Serpa
中科院分区：
文献类型：
--
作者：
William Camilo Ariza;A. Serpa
本文提出了一种基于人工神经网络的控制方法，应用于柔性结构的振动控制。采用直接逆控制方法。该方法包括使用人工神经网络作为控制器来识别设备的逆动态。提出了一个应用示例，并处理了两个问题变体。应用问题基于悬臂板模型。使用有限元方法获得板模型。对于第一个问题，控制器是使用全阶对象模型设计的。在第二个示例中，进行了模型简化，以评估该技术应用于具有动态不确定性的控制问题的性能。根据闭环系统的时间响应和频率响应来评估结果。为了比较使用基于人工神经网络的控制方法获得的结果，前面的例子也使用H ∞ 控制方法进行求解。所得结果表明，基于神经网络逆模型的控制方法可以有效解决此类问题。
In this article, a control method based on artificial neural networks applied to the vibration control of flexible structures is presented. The direct inverse control method is used. This method consists in the identification of the inverse dynamics of the plant using an artificial neural network to be used as the controller. An application example is proposed, and two problem variations are treated. The application problem is based on a cantilever plate model. The plate model is obtained using the finite element method. For the first problem, the controller is designed using the full-order plant model. In the second example, a model reduction is made to evaluate the performance of this technique applied to control problems with dynamic uncertainties. The results were evaluated according to the time response and frequency response of the closed-loop system. To compare the results obtained using the control method based on artificial neural networks, the previous examples were also solved using the H ∞ control method. The obtained results show that the control method based on the inverse model using neural networks is effective in solving this kind of problem.