An EKF based on an enhanced model for parameter estimation in bioprocesses

An EKF based on an enhanced model for parameter estimation in bioprocesses
复制标题

基于生物过程参数估计增强模型的 EKF

DOI：
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发表时间：
2001
期刊：
European Control Conference
影响因子：
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通讯作者：
D. Sbarbaro
D. Sbarbaro
中科院分区：
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文献类型：
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作者：
P. Ascendo;D. Sbarbaro

文献摘要

被引文献

相似文献

本文提出了一种用于估计生物过程动力学速率的扩展卡尔曼滤波器（EKF）。未知的动力学速率被建模为持续激励的线性系统的输出。滤波器的增益由Ricatti微分方程设计。利用李雅普诺夫函数分析了算法的稳定性和收敛性。为了说明这个观察员的应用，提出了一个单一的微生物培养的动力学速率的估计。
This work presents an Extended Kalman Filter (EKF) for estimating the kinetic rates in bioprocesses. The unknown kinetic rates are modeled as the output of a linear system persistently excited. The gain of the filter is designed by the Ricatti differential equation. The stability and convergence are analyzed using Lyapunov functions. To illustrate the application of this observer, the estimation of the kinetic rates of a single microbial culture is presented.