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Linear discrete-time state space realization of a modified quadruple tank system with state estimation using Kalman filter

机译:基于卡尔曼滤波的状态估计改进四重水箱系统的线性离散时间状态空间实现

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摘要

In this paper, we used the modified quadruple tank system that represents a multi-input-multi-output (MIMO) system as an example to present the realization of a linear discrete-time state space model and to obtain the state estimation using Kalman filter in a methodical mannered. First, an existing dynamics of the system of stochastic differential equations is linearized to produce the deterministic-stochastic linear transfer function. Then the linear transfer function is discretized to produce a linear discrete-time state space model that has a deterministic and a stochastic component. The filtered part of the Kalman filter is used to estimates the current state, based on the model and the measurements. The static and dynamic Kalman filter is compared and all results is demonstrated through simulations.
机译:在本文中,我们以代表多输入多输出(MIMO)系统的改进四重坦克系统为例,介绍了线性离散时间状态空间模型的实现并使用卡尔曼滤波器获得状态估计有条不紊地。首先,将随机微分方程系统的现有动力学线性化,以产生确定性-随机线性传递函数。然后将线性传递函数离散化,以产生具有确定性和随机成分的线性离散时间状态空间模型。卡尔曼滤波器的滤波部分用于基于模型和测量值来估计当前状态。比较了静态和动态卡尔曼滤波器,并通过仿真演示了所有结果。

著录项

  • 作者

    Mohd. Azam Sazuan Nazrah;

  • 作者单位
  • 年度 2017
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
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