Measure of disturbance rejection for a Neonate Monitoring System using adapted Neuro-Fuzzy inference system
Author(s): Awofolaju TT, Oladayo AO and Akanbi LO
Abstract: Temperature is a critical component of the environment since it significantly impacts human life, property, and product quality. A pleasant temperature is necessary for pleasant living. As a result, it is critical to monitor the temperature of humans, particularly newborn newborns less than 30 days, due to their low thermal stability. The temperature monitoring system for newborns enables the monitoring and regulation of neonatal heat levels. Adequate ambient warmth is critical for child care to sustain body heat. The typical Proportional Integral Derivative (PID) temperature controller, which is often employed, is well suited for stable systems. Additionally, there are issues with the extended settling period, the huge time constant, overshoot, and the difficulty in obtaining an appropriate mathematical model. The purpose of this project is to create a neural fuzzy-PID controller for monitoring neonatal temperature. A typical fuzzy proportional integral derivative (PID) controller was integrated with artificial neurons in the heating and cooling system design to manage the Neonate's temperature.
Awofolaju TT, Oladayo AO, Akanbi LO. Measure of disturbance rejection for a Neonate Monitoring System using adapted Neuro-Fuzzy inference system. Int J Comput Artif Intell 2021;2(1):57-61. DOI: 10.33545/27076571.2021.v2.i1a.27