A thermostatic control strategy based on multi-sensor data fusion and fuzzy-PID method

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI:10.1109/ICSENST.2016.7796326

Fei Shen, Ruqiang Yan

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引用次数: 1

Abstract

The steady temperature is vital to organ-saving out of body in a hypothermic machine perfusion (HMP) system. A thermostatic control strategy based on multi-sensor data fusion and fuzzy-PID method is proposed in this paper to improve the accuracy. Firstly, the basic frame of HMP system and the installation of sensors are expounded. Then the data fusion based on modified Bayes estimation is carried out to weaken the possible measurement error, resulting from the sensor faults and noise interference. Specially, the better error-recovery ability is proved in the cascaded Bayes algorithm. Secondly, the fuzzy and the fuzzy-PID (Proportion Integration Differentiation) controller are adopted respectively according to the difference of temperature-deviation. Here the former is designed to offer the control variation of compressor needed while the latter is to gain three control coefficients of PID algorithm. The dynamic and static tests indicate that the thermostatic control result meets the need of patients although it is also affected by some extra factors, such as the external temperature, flow speed of solution and working modes.

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一种基于多传感器数据融合和模糊pid方法的恒温控制策略

在低温机器灌注系统中，稳定的温度对器官保存至关重要。为了提高控制精度，提出了一种基于多传感器数据融合和模糊pid方法的恒温控制策略。首先，阐述了HMP系统的基本结构和传感器的安装。然后进行基于改进贝叶斯估计的数据融合，以减弱传感器故障和噪声干扰可能导致的测量误差。特别地，证明了级联贝叶斯算法具有较好的错误恢复能力。其次，根据温度偏差的不同，分别采用模糊控制器和模糊pid(比例积分微分)控制器。前者提供所需压缩机的控制变量，后者获得PID算法的三个控制系数。动态和静态试验表明，恒温控制结果满足患者的需要，但也受到一些额外因素的影响，如外部温度、溶液流速和工作模式。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2016 10th International Conference on Sensing Technology (ICST)

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