Non-fragile finite-time l(2) - l(infinity) state estimation for discrete-time neural networks with semi-Markovian switching and random sensor delays based on Abel lemma approach

Rakkiyappan R.; Maheswari K.; Sivaranjani K.; Joo Young Hoon

首页> 外文期刊>Nonlinear analysis. Hybrid systems: An International Multidisciplinary Journal >Non-fragile finite-time l(2) - l(infinity) state estimation for discrete-time neural networks with semi-Markovian switching and random sensor delays based on Abel lemma approach

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Non-fragile finite-time l(2) - l(infinity) state estimation for discrete-time neural networks with semi-Markovian switching and random sensor delays based on Abel lemma approach

机译：非易碎有限时间L（2） - L（Infinity）基于Abel Lemma方法的半月形交换和随机传感器延迟的离散时间神经网络的状态估计

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This paper focuses the non-fragile state estimation problem for a class of discrete-time neural networks with semi-Markov switching and unreliable communication links in finite time l(2) - l(infinity) sense that are caused due to the randomly occurring sensor nonlinearity, randomly occurring time delays and packet dropouts. By employing semi-Markovian switching with time-varying transition rates, a broader class of dynamical systems than the traditional Markovian jump linear systems is described. Then, based on the Abel lemma approach on finite sum inequalities, a non-fragile state estimator is obtained to ensure that the resulting error system is mean-square stochastically finite-time stable with a prescribed l(2 )- l(infinity) performance. Sufficient conditions for the gain of the state estimator are obtained through solving a set of linear matrix inequalities. Finally a numerical example is provided to substantiate the theoretical results. (C) 2018 Elsevier Ltd. All rights reserved.

机译：本文将一类具有半马尔可夫切换和有限时间L（2） - L（Infinity）意义上的不可靠的通信链路的非易碎状态估计问题重点是由于随机发生的传感器引起的非线性，随机发生的时间延迟和数据包丢失。通过采用具有时变的转换速率的半马尔可夫切换，描述了比传统的马尔科维亚跳跃线性系统的更广泛的动态系统。然后，基于有限和不平等的Abel Lemma方法，获得非易碎状态估计器以确保所产生的误差系统是平均方形有限的有限时间稳定，具有规定的L（2） - L（Infinity）性能。通过求解一组线性矩阵不等式来获得状态估计器的增益的充分条件。最后提供了一个数值例子以证实理论结果。（c）2018年elestvier有限公司保留所有权利。

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来源
《Nonlinear analysis. Hybrid systems: An International Multidisciplinary Journal》 |2018年第2018期|共20页
作者
Rakkiyappan R.; Maheswari K.; Sivaranjani K.; Joo Young Hoon;
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作者单位

Bharathiar Univ Dept Math Coimbatore 641046 Tamil Nadu India;

Kumaraguru Coll Technol Dept Math Coimbatore 641049 Tamil Nadu India;

Bharathiar Univ Dept Math Coimbatore 641046 Tamil Nadu India;

Kunsan Natl Univ Res Ctr Wind Energy Syst Gunsan South Korea;

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原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
关键词
Semi-Markov jump neural networks; Finite-time l(2) - l(infinity) state estimation; Abel lemma approach; Non-fragile estimator; Unreliable communication channels;

机译：半马尔可夫跳跃神经网络;有限时间L（2） - L（Infinity）状态估计;abel Lemma方法;非脆弱的估算器;不可靠的通信渠道;

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1. Non-fragile finite-time l(2) - l(infinity) state estimation for discrete-time neural networks with semi-Markovian switching and random sensor delays based on Abel lemma approach [J] . Rakkiyappan R., Maheswari K., Sivaranjani K., Nonlinear analysis. Hybrid systems: An International Multidisciplinary Journal . 2018,第期

机译：非易碎有限时间L（2） - L（Infinity）基于Abel Lemma方法的半月形交换和随机传感器延迟的离散时间神经网络的状态估计
2. Finite-time non-fragile state estimation for discrete neural networks with sensor failures, time-varying delays and randomly occurring sensor nonlinearity [J] . Li Jian-Ning, Xu Yu-Fei, Bao Wen-Dong, Journal of the Franklin Institute . 2019,第3期

机译：具有传感器故障，时变延迟和随机发生的传感器非线性的离散神经网络的有限时间非脆弱状态估计
3. Non-weighted H-infinity state estimation for discrete-time switched neural networks with persistent dwell time switching regularities based on Finsler's lemma [J] . Rakkiyappan R., Maheswari K., Sivaranjani K. Neurocomputing . 2017,第octa18期

机译：基于Finsler引理的具有持续停留时间切换规律的离散时间切换神经网络的非加权H-无穷状态估计
4. Non-fragile State Estimation for Discrete-Time Complex Networks with Randomly Occurring Time-Varying Delays [C] . Sunjie Zhang, Jingyang Mao, Derui Ding, Chinese Control Conference . 2017

机译：用于随机发生的时变延迟的离散时间复杂网络的非脆弱状态估计
5. Neural network sensor fusion: Creation of a virtual sensor for cloud-base height estimation. [D] . Pasika, Hugh Joseph Christopher. 2000

机译：神经网络传感器融合：创建用于云基高度估计的虚拟传感器。
6. Enhanced robust finite-time passivity for Markovian jumping discrete-time BAM neural networks with leakage delay [O] . C Sowmiya, R Raja, Jinde Cao, -1

机译：具有泄漏延迟的马尔可夫跳跃离散时间BAM神经网络的增强鲁棒有限时间无源性
7. H-infinity state estimation for discrete-time complex networks with randomly occurring sensor saturations and randomly varying sensor delays [O] . Ding, D, Wang, Z, Shen, B, 2012

机译：具有随机发生的传感器饱和和随机变化的传感器延迟的离散时间复杂网络的H-无穷状态估计

Non-fragile finite-time l(2) - l(infinity) state estimation for discrete-time neural networks with semi-Markovian switching and random sensor delays based on Abel lemma approach

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