[1]LI Gui-ying,WEI Ying,ZHANG Yang,et al.An adaptive neural network L2gain controller for nonlinear systems with uncertainty[J].CAAI Transactions on Intelligent Systems,2009,4(4):357-362.
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An adaptive neural network L2gain controller for nonlinear  systems with uncertainty

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 4 Number of periods: 2009 4 Page number: 357-362 Column: 学术论文—机器学习 Public date: 2009-08-25
Title:
An adaptive neural network L2gain controller for nonlinear  systems with uncertainty
Author(s):
LI Gui-ying;  WEI Ying;  ZHANG Yang;  SUN Lai-jun
Laboratory of Electrical Engineering ＆ Automation, Heilongjiang University, Harbin 150080, China
Keywords:
L2gain;  neural network control;  HJI inequality
CLC:
TP273
DOI:
-
Abstract:
A scheme for an adaptive neural network L2gain controller was proposed for nonlinear systems with uncertainty. By combining the HamiltonJacobiIssacs (HJI) inequality with an adaptive neural network, limitations on the precision of previous models can be effectively overcome. With this controller, errors from the model were fitted by the neural network. In order to compensate for the fitting errors, a compensation controller and an adaptive law for the weights of the neural network were introduced. By online adaptive adjustment of these weights, L2gain performance of the closedloop system could be guaranteed.Simulation results are shown to demonstrate the effectiveness and the advantages of the proposed approach. To avoid the limitation of the precision model of the plant in the common approach.
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