Closed loop automated drug infusion regulation based on optimal 2-DOF TID control approach for the mean arterial blood pressure

This work aims to design an optimal controller for regulating mean arterial blood pressure (MAP) during the cardiac cycle in surgical and post-surgical conditions to enhance automated drug infusion. MAP controllers must address uncertainties like external disturbances, time-varying parameters, and noise. Thus, closed-loop control is essential to normalize MAP regardless of the patient's pharmacokinetics during surgery. A two-degree-of-freedom tilt integral derivative (2-DOF TID) controller, tuned by the Chernobyl Disaster Optimizer (CDO) algorithm, is proposed to dynamically adjust sodium nitroprusside (SNP) infusion rates in various conditions. The performance of this 2-DOF TID controller is compared with CDO-based PID, 2-DOF PID, and TID controllers. The results demonstrate the effectiveness and robustness of the proposed controller in achieving and maintaining MAP at 100 mmHg. All controllers are evaluated on different patient responses, including fixed and time-varying sensitivities, to SNP infusion, external disturbances, and noise. The study reveals which controller performs best in terms of overshoot, settling time, error, disturbance rejection, and anti-interference ability, confirming the 2-DOF TID controller as a strong candidate for automated drug infusion systems in clinical settings.