Identification of time-varying pH processes using sinusoidal signals
Identification of time-varying pH processes using sinusoidal signals
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DOI：
10.1016/j.automatica.2004.11.003
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发表时间：
2005-04
期刊：
影响因子：
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通讯作者：
A. Kalafatis;Liuping Wang;W. R. Cluett
中科院分区：
文献类型：
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作者：
A. Kalafatis;Liuping Wang;W. R. Cluett
本文提出了一种基于Wiener模型结构的时变非线性pH过程辨识方法。该算法产生滴定曲线的在线估计，其中该静态非线性的形状由于工艺进料流的弱物质浓度和/或组成的变化而变化。辨识方法是基于递归最小二乘算法，线性动态的频率采样滤波器模型和逆静态非线性的多项式表示。对照试剂流速的正弦信号用于生成输入-输出数据沿着自动调节输入平均水平的方法，以确保在感兴趣的pH操作区域中识别滴定曲线。从pH过程中得到的实验结果来说明所提出的方法的性能。这些结果的pH值控制问题的应用进行了概述。
This paper presents an approach to the identification of time-varying, nonlinear pH processes based on the Wiener model structure. The algorithm produces an on-line estimate of the titration curve, where the shape of this static nonlinearity changes as a result of changes in the weak-species concentration and/or composition of the process feed stream. The identification method is based on the recursive least-squares algorithm, a frequency sampling filter model of the linear dynamics and a polynomial representation of the inverse static nonlinearity. A sinusoidal signal for the control reagent flow rate is used to generate the input–output data along with a method for automatically adjusting the input mean level to ensure that the titration curve is identified in the pH operating region of interest. Experimental results obtained from a pH process are presented to illustrate the performance of the proposed approach. An application of these results to a pH control problem is outlined.