文章基本信息

标题：Improving Transient Response in Adaptive Control of Nonlinear Systems
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作者：Koshy George ; Karpagavalli Subramanian ; Nagashree Sheshadhri 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：1
页码：658-663
DOI：10.1016/j.ifacol.2016.03.131
语种：English
出版社：Elsevier
摘要：AbstractAn important requirement in control systems is an acceptable transient response. When the underlying dynamical systems are unknown, a factor that contributes is how fast an algorithm can identify them. It is well-known that the back propagation algorithm has rather poor convergence properties. Consequently, it sometimes takes several thousand iterations before the transient response is satisfactory. In this paper, we show that a sequential variant of the extreme learning machine considerably improves the transient response.
关键词：KeywordsAdaptive ControlNonlinear SystemsNeural NetworksFeed-forward NetworksParameter Estimation