基于最大灵敏度神经网络的在线学习控制

2014 13th Mexican International Conference on Artificial Intelligence Pub Date : 2014-11-16 DOI:10.1109/MICAI.2014.24

Mario Aguilera-Ruiz, L. Torres-Treviño, A. Rodríguez-Liñán

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引用次数: 2

摘要

本文提出了一种最大灵敏度神经网络，用于构造一个对象逆控制器的在线学习系统。这个神经网络被训练来学习植物对不同随机输入的反应。一旦网络被训练，它就可以用来控制工厂达到期望的输出。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Control by Online Learning Using a Maximum Sensibility Neural Network

In this paper, a maximum sensibility neural network is proposed to make an online learning system of a inverse controller of a plant. This neural network is trained to learn the response of the plant to different random inputs. Once the network is trained, it can be used to control the plant to a desired output.

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2014 13th Mexican International Conference on Artificial Intelligence

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