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Artificial neural network for piezoelectric control systems

机译:压电控制系统人工神经网络

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This paper presents a neural network controller for a piezoelectric controlled structure by emulating the control performance of a Linear Quadratic Gaussian (LQG) controller. The configuration of the Artificial Neural Network (ANN) is simple, yet it is efficient in terms of its high learning speed and good generalization ability. A case study is presented to demonstrate the performance of the ANN controller versus the LQG controller. The test results for different disturbances on the structure show excellent agreement between the ANN and LQG controllers.
机译:本文通过模拟线性二次高斯(LQG)控制器的控制性能,提出了一种用于压电控制结构的神经网络控制器。人工神经网络(ANN)的配置很简单,但在其高学习速度和良好的概率能力方面是有效的。提出了一个案例研究以证明ANN控制器与LQG控制器的性能。结构上不同干扰的测试结果显示了ANN和LQG控制器之间的良好协议。

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