[1]李钧涛,贾英民.基于自适应神经网络的一类不确定非线性系统的鲁棒H∞控制[J].智能系统学报,2007,2(06):54-59.
 LI Jun-tao,JIA Ying-min.Robust H∞ control for a class of uncertain nonlin ear systems based on adaptive neural networks[J].CAAI Transactions on Intelligent Systems,2007,2(06):54-59.
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基于自适应神经网络的一类不确定非线性系统的鲁棒H控制(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第2卷
期数:
2007年06期
页码:
54-59
栏目:
学术论文—智能系统
出版日期:
2007-12-25

文章信息/Info

Title:
Robust H∞ control for a class of uncertain nonlin ear systems based on adaptive neural networks
文章编号:
1673-4785(2007)06-0054-06
作者:
李钧涛 贾英民
北京航空航天大学第七研究室,北京 100083
Author(s):
LI Jun-taoJIA Ying-min
The Seventh Research Division, Beihang University, Beijing 100 083, China
关键词:
H控制自适应神经网络非线性系统机器人系统
Keywords:
H∞ control adaptive neural network nonlinear systems robotic systems
分类号:
TP273
文献标志码:
A
摘要:
针对一类不确定非线性多输入时变系统,提出了一种新的鲁棒H∞控制方案.通过引入2个自适应神经网络逼近器,提出了一个简化的HamiltonJacobilike不等式,并据此设计了非线性H∞控制器和匹配不确定项补偿控制器,消除了输入摄动项和估计器最优逼近误差的有界性假设.机器人系统的鲁棒跟踪控制仿真算例证实了所提出控制方案的有效性.
Abstract:
This paper presents a novel robust H∞ control scheme for a class of uncer tain nonlinear multiinput timevarying systems. A simplified HamiltonJacobi li ke inequality was proposed by introducing two adaptive neural network approximat ors. Then, a nonlinear H∞ controller and a compensation controller for match ed uncertainties were designed, thus eliminating the boundedness assumpti ons of the input perturbation term and the optimal approximation errors in the estimator. Finally, a simulation of the robost tracking control for robotic syst em was run that verified t he research results.

参考文献/References:

[1]WANG W Y,CHAN M L,HSU C C J, et al. H∞ Tracking ba sed sliding mode control for uncertain nonlinear systems via an adaptive fuzzyneural appr oach[J]. IEEE Transactions on Systems, Man, and Cyber netics,2002,32(3):483- 492.
[2]CHEN B S,LEE C H,CHANG Y C. Tracking design of uncertain nonl in ear SISO systems: adaptive fuzzy approach [J]. IEEE Trans Fuzzy Syst, 1996(4) :32-43.
[3]LIN T C,WANG C H,LIU H L.Observerbased indirect adaptive fu z zyneural tracking control for nonlinear SISO systems using VSS and approach [ J]. Fuzzy Sets Syst,2004,143:211-232.
[4]ISIDORI A,ASTOLFI A. Disturbance attenuation and control via measur ement feedback in nonlinear systems [J]. IEEE Trans Autom Contr, 1992,37(11):1283-1293.
[5]CHANG Y C.Intelligent robust control for uncertain nonli near timevaryi ng systems and its application to robotic systems [J]. IEEE Transactions on Systems, Man, and Cybernetics,2005, 35(6):1108-1119.
[6]SHEN T L,TAMURA K. Robust control of uncertain nonlinear system via state feedback [J]. IEEE Trans Robot Autom,2004,40(4):766-768.
[7]LEU Y G,WANG W Y,LEE T T. Robust adaptive fuzzyneural control lers for uncertain nonlinear systems [J]. IEEE Trans Robot Autom,1999,15:805 -817.
[8]PARK J H,SEO S J,PARK G T. Robust adaptive fuzzy controller fo r nonlinear systems using estimation of bounds for approximation errors [J]. F uzzy Sets Syst,2003,133(1):19-36.
[9]LIN W. Global robust stabilization of minimumphase nonlinear systems wi th uncertainty [J]. Automatica,1997,33(3):453-462.
[10]KHALIL H K. Adaptive output feedback control of nonlinear systems re pre sented by inputoutput models [J]. IEEE Trans Autom Contr, 1996,41(2):177-1 78.

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备注/Memo

备注/Memo:
收稿日期:2007-05-14.
基金项目:
国家自然科学基金资助项目(60374001);
教育部博士点基金资助项目(20030006003);
国防基础研究资助项目(A21 2006 1303)
作者简介: 
李钧涛,男,1978年生,博士研究生.主要研究方向为智能控制. E-mail:Juntaolimail@yahoo.com.cn. 
贾英民,男,1958年生,教授,博士生导师,教育部“长江学者”特聘教授,国家杰出青年科学基金获得者,国家“百千万人才工程” 第一、二层次人选,主要研究方向为鲁棒控制、自适应控制、智能控制及其在车辆系统和工业过程中的应用.E-mail:ymjia@buaa.edu.cn.
更新日期/Last Update: 2009-05-09