带有随机发生非线性的时变动态系统非脆弱递归状态估计
Nonfragile Recursive State Estimation for Time-Varying Dynamic Systems with Random Nonlinearity
摘要: 本文研究了一类带有随机发生非线性的时变动态系统非脆弱递归状态估计问题。本系统包含以下几种网络现象：系统的不确定性、随机发生非线性和非脆弱，其中随机发生非线性通过一个服从伯努利分布的随机变量来刻画，非脆弱满足的是范数有界不确定性。本文的目的是提出一种针对随机发生非线性的鲁棒非脆弱状态估计算法。由于估计误差协方差矩阵不能精确地表达出来，于是我们找到误差协方差矩阵的上界，并且通过设计滤波增益矩阵使得该上界的迹达到最小。最后，给出一个数值仿真来说明该算法的实用性。
Abstract: A class of time-varying dynamic systems with random nonlinearity are studied in this paper. This system contains the following network phenomena: The system’s uncertainty, random occurrence non-linearity and non-fragility, among which random occurrence non-linearity is represented by a random variable obeying Bernoulli distribution, non-fragility satisfies the norm bounded uncer-tainty. The aim of this paper is to propose a robust non-fragile state estimation algorithm for sto-chastic nonlinearity. Since the estimated error covariance matrix cannot be expressed accurately, we find the upper bound of the error covariance matrix and minimize the trace of the upper bound by designing the filter gain matrix. Finally, a numerical simulation is given to illustrate the practi-cability of the algorithm.
文章引用：计东海, 王洪大. 带有随机发生非线性的时变动态系统非脆弱递归状态估计[J]. 应用数学进展, 2019, 8(1): 71-80. https://doi.org/10.12677/AAM.2019.81008

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