文献类型：期刊文献

中文题名：Adaptive Neural Control for a Class of Low-triangular-structured Nonlinear Systems with H-∞ Performance Analysis

英文题名：Adaptive neural control for a class of low-triangular-structured nonlinear systems with H- ∞performance analysis

作者：Wang, Hui-Feng[1]; Du, Hong-Bin[1]

机构：[1] Automation Department, East China University of Science and Technology, Shanghai 200237, China

年份：2008

卷号：25

期号：4

起止页码：425

中文期刊名：Journal of Donghua University(English Edition)

外文期刊名：Journal of Donghua University (English Edition)

收录：EI(收录号：20090611897401);Scopus

基金：Shanghai Leading Academic Discipline Project(B504)

语种：英文

中文关键词：adaptive neural control ;variable structure control ; nonlinear system ;backstep ping ;triangular structure ;H-∞ performance

外文关键词：Adaptive control systems - Feedback - Variable structure control

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.
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 C1, 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 htw is verified via simulation.