Fractional Order Jellyfish Optimizer on PID cascade controller for new born incubator system

Abstract

This paper presents a cascade PID controller developed for the simultaneous regulation of skin and air temperatures in neonatal incubators, thereby ensuring a neutral thermal environment. A critical challenge in cascade control is the optimal tuning of the primary and secondary controllers. To address this, we introduce a Fractional Order Jellyfish Search Optimizer (FJSO) that leverages fractional calculus to overcome the convergence limitations inherent in the standard jellyfish optimizer. Experimental results indicate that FJSO achieves a 12% reduction in the mean solution value and a 15% improvement in the best-found solution relative to the next-best algorithm, as evidenced by the best, mean, and standard deviation metrics. Furthermore, simulation studies using a Simulink model of neonatal thermal balance demonstrate that the cascade PID controller tuned with FJSO outperforms a single PID controller, particularly in transient and steady-state responses. Performance assessments based on standard control indices, such as the Integral of Absolute Error (IAE) and disturbance rejection, reveal improvements of approximately 17.62% and 79.87%, respectively, over classical control approaches.