Neural-net computing and the intelligent control of systems
作者:
YOH-HAN PAO,
STEPHENM. PHILLIPS,
DEJANJ. SOBAJIC,
期刊:
International Journal of Control
(Taylor Available online 1992)
卷期:
Volume 56,
issue 2
页码: 263-289
ISSN:0020-7179
年代: 1992
DOI:10.1080/00207179208934315
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
In this article, we are concerned with neural-nets which canlearnto control systems in accordance with a guiding intent, and can alsolearnhow to formulate that control strategy or intent. The overall task of systems control is viewed as being carried out by four components, these being the predictive monitoring net, the control action generator net, the objective function net and the optimization net. This approach and perspective are described and illustrated in this article. In our examples, we show that systems identification can indeed be achieved in the presence of noise and that optimal control can be formulated in a learning mode, by neural nets.
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