Joint state and fault estimation for nonlinear complex networks with mixed time-delays and uncertain inner coupling: non-fragile recursive method

IF 3.2 Q2 AUTOMATION & CONTROL SYSTEMS
Shuyang Feng, Huijun Yu, Chaoqing Jia, Pingping Gao
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引用次数: 13

Abstract

In this paper, the non-fragile joint state and fault estimation problem is investigated for a class of nonlinear time-varying complex networks (NTVCNs) with uncertain inner coupling and mixed time-delays. Compared with the constant inner coupling strength in the existing literature, the inner coupling strength is permitted to vary within certain intervals. A new non-fragile model is adopted to describe the parameter perturbations of the estimator gain matrix which is described by zero-mean multiplicative noises. The attention of this paper is focussed on the design of a locally optimal estimation method, which can estimate both the state and the fault at the same time. Then, by reasonably designing the estimator gain matrix, the minimized upper bound of the state estimation error covariance matrix (SEECM) can be obtained. In addition, the boundedness analysis is taken into account, and a sufficient condition is provided to ensure the boundedness of the upper bound of the SEECM by using the mathematical induction. Lastly, a simulation example is provided to testify the feasibility of the joint state and fault estimation scheme.
混合时滞不确定内耦合非线性复杂网络的联合状态与故障估计:非脆弱递推方法
研究了一类具有不确定内耦合和混合时滞的非线性时变复杂网络(NTVCNs)的非脆性连接状态和故障估计问题。与现有文献中恒定的内耦合强度相比,允许内耦合强度在一定的区间内变化。采用一种新的非脆弱模型来描述由零均值乘性噪声描述的估计器增益矩阵的参数扰动。本文的重点是设计一种局部最优估计方法,该方法可以同时对状态和故障进行估计。然后,通过合理设计估计器增益矩阵,得到状态估计误差协方差矩阵(SEECM)的最小上界。此外,考虑了有界性分析,利用数学归纳法给出了保证SEECM上界有界性的充分条件。最后,通过仿真实例验证了该联合状态和故障估计方案的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Systems Science & Control Engineering
Systems Science & Control Engineering AUTOMATION & CONTROL SYSTEMS-
CiteScore
9.50
自引率
2.40%
发文量
70
审稿时长
29 weeks
期刊介绍: Systems Science & Control Engineering is a world-leading fully open access journal covering all areas of theoretical and applied systems science and control engineering. The journal encourages the submission of original articles, reviews and short communications in areas including, but not limited to: · artificial intelligence · complex systems · complex networks · control theory · control applications · cybernetics · dynamical systems theory · operations research · systems biology · systems dynamics · systems ecology · systems engineering · systems psychology · systems theory
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