估计员
控制理论(社会学)
离散化
卡尔曼滤波器
偏微分方程
软传感器
数学
常微分方程
数学优化
计算机科学
微分方程
统计
数学分析
人工智能
控制(管理)
过程(计算)
操作系统
作者
Lu Zhang,Junyao Xie,Stevan Dubljević
摘要
Abstract The state estimation and sensor placement for a continuous pulp digester with delayed measurements are investigated. The underlying model of interest is heat transfer in a pulp digester modeled by two coupled hyperbolic partial differential equations and an ordinary differential equation. Output measurements are considered with delay due to the possible low sampling rate. The Cayley–Tustin transformation is utilized to realize model time discretization in a late lumping manner which does not account for any type of spatial approximation or model reduction. The discrete Kalman filter is applied to estimate the system states using the delayed measurements. The selection of sensor location is addressed along with estimator design accounting for the delayed measurements and investigated by minimizing the variance of estimation error. The performance of the state estimator is evaluated, and the sensor placement is analyzed through simulation studies, which offers a planning view of sensor location in industrial applications.
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