Optimization of PIDD2-FLC for blood glucose level using particle swarm optimization with linearly decreasing weight

In this paper, a Proportional-Integral-Differential plus second order derivative Fuzzy Logic Controller (PIDD2-FLC) is implemented aiming to maintain blood glucose level (BGL) normal in type I diabetic subjects. In type I diabetes, insulin-secreting cells are destroyed and, hence, patient depends on external insulin to maintain BGL. The suggested controller is responsible for driving a micro-pump that injects the diabetic patient with proper insulin dose, and a continuous BGL sensor is used for feedback. The nonlinear patient model used is the two-delay differential model, and the reference model for BGLs considered as in the treatment model planned using the two-delay differential model with oscillatory behavior. Particle Swarm Optimization with Linearly Decreasing Weight (LDW-PSO) algorithm is used to optimize the proposed controllers to match the reference model performance. Finally, a comparison is held between the optimized controller with other FLC controllers structures taking into consideration the normal and abnormal conditions. PIDD2-FLC with seven linguistic fuzzy membership functions (MFs) was found to have the best performance overall under different examining conditions. (C) 2020 Elsevier Ltd. All rights reserved.