A Recursive Least Squares based Direct Self-Tuning PID for Blood Pressure Control in Hypertensive Emergencies

Abstract

Hypertensive emergencies require extensive medical involvement to prevent adverse health outcomes. Automated systems can streamline procedures and enable professionals to administer seasoned treatments to hypertensive patients. However, utilizing fixed-gain controllers for individuals with unpredictable traits, such as heightened sensitivity, might lead to undesirable responses. This study introduces a Recursive Least Squares-based adaptive PID (Proportional-Integral- Derivative) controller for hypertensive emergencies, comparing three forgetting factors. The goal is to design a controller that adapts to patient profiles using algorithmic learning and clinical guidelines. Finally, the proposed direct adaptive controller with time-varying forgetting factor demonstrated effectiveness in reducing blood pressure across a range of simulated patient profiles.