Comparison of the Performances between Fuzzy and Fuzzy PID Temperature Controllers in Phototherapy Incubator for Infant Jaundice Treatment

Fuzzy control demonstrates remarkable flexibility in addressing nonlinear issues and formulating algorithms through an if-then rule pattern. However, a fuzzy controller requires a substantial number of fuzzy grades, leading to increase many rules for achieving higher accuracy. This study introduces an efficient Fuzzy-PID (FPID) controller designed to manage the degree of membership in the fuzzy inference system, specifically for temperature control in a phototherapy incubator. Comparative analyses of the performance of the fuzzy and FPID controllers were conducted in a computer simulation. The FPID controller exhibited significantly superior performance, notably reducing the time delay compared to the fuzzy controller. In the simulation, the delays for the FPID and PID controllers were approximately 0.5 and 5 seconds, respectively. The equivalent fine-tuning of the PID controller for the fuzzy logic controller is straightforward to implement and offers high performance in regulating the temperature of the incubator. Consequently, the simulation results provide valuable insights for the design of modern phototherapy incubators used in the treatment of infant jaundice.

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Published
2024-11-29
DOI
https://doi.org/10.1109/irac63143.2024.10871850
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Comparison of the Performances between Fuzzy and Fuzzy PID Temperature Controllers in Phototherapy Incubator for Infant Jaundice Treatment

Miaoxian Zhou, Bing‐Yuh Lu, Zupeng Li, Lei Liang et al.
IoT-based Smart Home Systems
article

Comparison of the Performances between Fuzzy and Fuzzy PID Temperature Controllers in Phototherapy Incubator for Infant Jaundice Treatment

Miaoxian Zhou, Bing‐Yuh Lu, Zupeng Li, Lei Liang, Guangming Xu, Ruilong Huang
article en

Abstract

Fuzzy control demonstrates remarkable flexibility in addressing nonlinear issues and formulating algorithms through an if-then rule pattern. However, a fuzzy controller requires a substantial number of fuzzy grades, leading to increase many rules for achieving higher accuracy. This study introduces an efficient Fuzzy-PID (FPID) controller designed to manage the degree of membership in the fuzzy inference system, specifically for temperature control in a phototherapy incubator. Comparative analyses of the performance of the fuzzy and FPID controllers were conducted in a computer simulation. The FPID controller exhibited significantly superior performance, notably reducing the time delay compared to the fuzzy controller. In the simulation, the delays for the FPID and PID controllers were approximately 0.5 and 5 seconds, respectively. The equivalent fine-tuning of the PID controller for the fuzzy logic controller is straightforward to implement and offers high performance in regulating the temperature of the incubator. Consequently, the simulation results provide valuable insights for the design of modern phototherapy incubators used in the treatment of infant jaundice.

Guangdong University of Petrochemical Technology (CN)
Guangdong University of Petrochemical Technology, National Natural Science Foundation of China
Zero hunger
Openalex Percentile: Top 75%
IoT-based Smart Home Systems
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Comparison of the Performances between Fuzzy and Fuzzy PID Temperature Controllers in Phototherapy Incubator for Infant Jaundice Treatment — Miaoxian Zhou, Bing‐Yuh Lu, et al. · (2024) | TGRS Research Map | TGRS