采用参数化神经网络设计控制器

M. Hasheminejad, J. Murata, K. Hirasawa
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引用次数: 1

摘要

采用一种内部结构更灵活的神经网络来设计更好的控制器。参数神经网络(PNN)通过适当设置参数,可以同时明确地表示线性和非线性关系。在许多情况下,我们有一些关于系统的信息,使我们能够为它建立一个线性控制器。当然,这对于处理非线性植物是不够的。使用PNN,我们可以制作一个互补的线性化控制器,然后,在开始学习后,以在线的方式将其扩展为非线性主导控制器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Controller design using parametric neural networks
A neural network (NN) of a more flexible internal structure than usual is used to design a better controller. A parametric NN (PNN) can represent both linear and nonlinear relationships explicitly and simultaneously by setting its parameters appropriately. In many cases we have some information about the system which enable us to build a linear controller for it. But of course this is not enough for treating nonlinear plants. Using PNN we could make a complimentary linearized controller and then, after starting the learning, in an online manner it will be extended to a nonlinear dominant controller.
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