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Adaptive Neural Control for a Class of Low-triangular-structured Nonlinear Systems with H-∞ Performance Analysis
引用本文:王慧锋,杜红彬.Adaptive Neural Control for a Class of Low-triangular-structured Nonlinear Systems with H-∞ Performance Analysis[J].东华大学学报(英文版),2008,25(4):425-433.
作者姓名:王慧锋  杜红彬
作者单位:Automation Department,East China University of Science and Technology
基金项目:Foundation item: Shanghai Leading Academic Discipline Project (B504) Acknowledgements The work was supported by National Natural Science Foundation of China under Grant 60704013. The authors would like to thank Professor S. S. Ge of National University of Singapore, for the insight instructions and suggestions.
摘    要:In this paper, a neural-network-based variable structure control scheme is presented for a class of nonlinear systems with a general low triangular structure. The proposed variable structure controller is proved to be Cl, thus can be applied for backstepping design, which has extended the scope of previous nonlinear systems in the form of strict-feedback and pure-feedback. With the help of neural network approximator, H-∞ performance analysis of stability is given. The effectiveness of proposed control law is verified via simulation.

关 键 词:自适神经控制  变结构控制  非线性系统  三角结构

Adaptive Neural Control for a Class of Low-triangular-structured Nonlinear Systems with H-∞ Performance Analysis
WANG Hui-feng,DU Hong-bin Automation.Adaptive Neural Control for a Class of Low-triangular-structured Nonlinear Systems with H-∞ Performance Analysis[J].Journal of Donghua University,2008,25(4):425-433.
Authors:WANG Hui-feng  DU Hong-bin Automation
Institution:Automation Department, East China University of Science and Technology, Shanghai 200237, China
Abstract:adaptive neural control variable structure control nonlinear system backstep ping triangular structure H-∞ performance
Keywords:adaptive neural control  variable structure control  nonlinear system  backstep ping  triangular structure  H-∞ performance
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