Robust adaptive control based on neural network for a class of uncertain nonlinear systems - 文章详情页

作者：

Ningning, Li (Ningning, Li.) | Su, Song (Su, Song.)

收录：

EI Scopus

摘要：

It　is　a　critical　problem　in　the　neural　network　adaptive　control　system　to　attenuate　the　influence　of　external　disturbance　or　unmodeled　dynamics　and　improve　the　robustness.　In　this　paper,　a　novel　robust　adaptive　control　based　on　neural　network　for　unknown　nonlinear　dynamical　systems　with　bounded　disturbances　or　unmodeled　dynamics　was　proposed.　It　was　realized　by　using　adaptive　forecasting　and　the　recursive　forgetting　factor　least　square　method,　also　the　stability　of　system　was　guaranteed　by　a　robust　controller.　The　validity　of　this　control　strategy　was　demonstrated　via　simulation　results.　©　2006　IEEE.

关键词：

Robustness (control systems) Robust control Least squares approximations Neural networks Adaptive control systems Nonlinear systems Uncertain systems Dynamical systems

作者机构：

[ 1 ] [Ningning, Li]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022
[ 2 ] [Su, Song]Department of Information Sciences, National Natural Science Foundation of China, Beijing 100085

通讯作者信息：

电子邮件地址：

linn@emails.bjut.edu.cn

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