TY - GEN
T1 - A thermostatic control strategy based on multi-sensor data fusion and fuzzy-PID method
AU - Shen, Fei
AU - Yan, Ruqiang
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/22
Y1 - 2016/12/22
N2 - 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.
AB - 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.
KW - HMP system
KW - data fusion
KW - fuzzy-PID controller
KW - modified Bayes estimation
KW - thermostatic control
UR - https://www.scopus.com/pages/publications/85010039010
U2 - 10.1109/ICSensT.2016.7796326
DO - 10.1109/ICSensT.2016.7796326
M3 - 会议稿件
AN - SCOPUS:85010039010
T3 - Proceedings of the International Conference on Sensing Technology, ICST
BT - 2016 10th International Conference on Sensing Technology, ICST 2016
PB - IEEE Computer Society
T2 - 10th International Conference on Sensing Technology, ICST 2016
Y2 - 11 November 2016 through 13 November 2016
ER -