Stochastically stable robust observer for uncertain chaotic systems with system and measurement noises

M. Ayati
{"title":"Stochastically stable robust observer for uncertain chaotic systems with system and measurement noises","authors":"M. Ayati","doi":"10.1109/ICCIAUTOM.2011.6356821","DOIUrl":null,"url":null,"abstract":"This paper presents a new chaos synchronization scheme based on the proposed stochastic adaptive sliding mode observer. The observer overcomes the drive system model uncertainties and unknown parameters to recover the drive system chaotic states form a scalar noisy coupling signal. Using the appropriate adaptation low the unknown parameters of the drive system are estimated and used to boost the state estimations. In addition, drive system state noise, channel noise, and measurement noise, are considered and the system and observer are modeled via stochastic differential equations. Stochastic stability of the drive-response system is proved through several theorems. These theorems guarantee that the mean values of the state estimation errors converge to zero as time goes to infinity. In the observer the adaptive sliding mode gains are always nonsingular even when the estimation error goes to zero. Presented numerical simulations confirm the effectiveness of the proposed observer and chaos synchronization scheme.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2nd International Conference on Control, Instrumentation and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIAUTOM.2011.6356821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper presents a new chaos synchronization scheme based on the proposed stochastic adaptive sliding mode observer. The observer overcomes the drive system model uncertainties and unknown parameters to recover the drive system chaotic states form a scalar noisy coupling signal. Using the appropriate adaptation low the unknown parameters of the drive system are estimated and used to boost the state estimations. In addition, drive system state noise, channel noise, and measurement noise, are considered and the system and observer are modeled via stochastic differential equations. Stochastic stability of the drive-response system is proved through several theorems. These theorems guarantee that the mean values of the state estimation errors converge to zero as time goes to infinity. In the observer the adaptive sliding mode gains are always nonsingular even when the estimation error goes to zero. Presented numerical simulations confirm the effectiveness of the proposed observer and chaos synchronization scheme.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
具有系统噪声和测量噪声的不确定混沌系统的随机稳定鲁棒观测器
本文提出了一种基于随机自适应滑模观测器的混沌同步方案。观测器克服了驱动系统模型的不确定性和未知参数,恢复了驱动系统的混沌状态,形成标量噪声耦合信号。采用适当的自适应方法对驱动系统的未知参数进行估计,并利用未知参数增强系统的状态估计。此外,还考虑了驱动系统的状态噪声、通道噪声和测量噪声,并通过随机微分方程对系统和观测器进行了建模。通过几个定理证明了驱动-响应系统的随机稳定性。这些定理保证了状态估计误差的均值在时间趋于无穷时收敛于零。在观测器中,即使估计误差趋近于零,自适应滑模增益也始终是非奇异的。仿真结果验证了该观测器和混沌同步方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Optimal design of adaptive interval type-2 fuzzy sliding mode control using Genetic algorithm Constrained model predictive control of PEM fuel cell with guaranteed stability Optimal control of an autonomous underwater vehicle using IPSO_SQP algorithm Design of an on-line recurrent wavelet network controller for a class of nonlinear systems Exact pupil and iris boundary detection
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1