Incorporating Known Plant Characteristics into Artificial Neural Networks for Dynamic System Identification and Control With Electrically Commutated Machine Applications

这个项目的主要重点是使用人工神经网络（ANNs）来识别和控制未知的非线性动态系统。然而，一般来说，人们对这种植物知之甚少。这项研究涉及到“灰色层”的使用，它有助于将未知植物的已知特征整合到人工神经网络中。该方法的收敛特性比传统方法好几个数量级。采用了最先进的智能控制和自适应控制技术，并在电动换向机器的背景下展示了它们的应用。* * * / /

The primary emphasis of this project is on the use of artificial neural networks (ANNs) for identification and control of unknown nonlinear dynamic systems. However, generally much is known about the plant. This research involves the use of a "gray layer" which facilitates the integration of known characteristics of the otherwise unknown plant into an ANN. The convergence characteristics using this novel technique are of several orders of magnitude better than the conventional schemes. Both state of the art intelligent control and adaptive control technologies are used, and their application is demonstrated in the context of electrically commutated machines.*** //