文献类型：期刊文献

英文题名：NN-based output feedback adaptive variable structure control for a class of non-affine nonlinear systems: A nonseparation principle design

作者：Du, Hongbin[1];Chen, Xiaochuan[2]

机构：[1]E China Univ Sci & Technol, Dept Automat, Shanghai 200237, Peoples R China;[2]Donghua Univ, Mech Engn Coll, Shanghai 201620, Peoples R China

年份：2009

卷号：72

期号：7-9

起止页码：2009

外文期刊名：NEUROCOMPUTING

收录：;EI(收录号：20091111957649);WOS:【SCI-EXPANDED(收录号:WOS:000264993200067)】；

基金：This work was supported by the National Nature Science Foundation of China under Grant 60704013. The author would like to thank Prof. H.K. Khalil for the helpful enlightenment about the separation principle designs and Prof. Shuzhi Sam Ge for the important suggestions.

语种：英文

外文关键词：Adaptive variable structure control; Output feedback; Nonlinear systems; Parametrization; Observer; Non-separation principle design

摘要：Based on non-separation principle design and the application of implicit Function Theorem, Mean Value Theorem, neural network parametrization and a simple linear observer, a new adaptive variable structure output feedback control is addressed for a class of non-affine nonlinear systems. In the presented scheme, many restrictive conditions, such as Lipschitz assumption, SPR (strictly positive realness) condition and contracting assumption are not required with the help of neural network parametrization. One of the main purposes of this work is to find out the relationships between the design parameters for observer and controller, and how to choose these design parameters in non-separation principle way. Semi-globally uniformly ultimate boundedness for the steady-state and transient performance is provided, and simulations verify the effectiveness of the proposed scheme. (c) 2009 Elsevier B.V. All rights reserved.