In Silico Evaluation of a Physiological Controller for a Rotary Blood Pump Based on a Sensorless Estimator

Abstract

In this study, we present a sensorless, robust, and physiological tracking control method to drive the operational speed of implantable rotary blood pumps (IRBPs) for patients with heart failure (HF). The method used sensorless measurements of the pump flow to track the desired reference flow (Qr). A dynamical estimator model was used to estimate the average pump flow (Q^est) based on pulse-width modulation (PWM) signals. A proportional-integral (PI) controller integrated with a fuzzy logic control (FLC) system was developed to automatically adapt the pump flow. The Qr was modeled as a constant and trigonometric function using an elastance function (E(t)) to achieve a variation in the metabolic demand. The proposed method was evaluated in silico using a lumped parameter model of the cardiovascular system (CVS) under rest and exercise scenarios. The findings demonstrated that the proposed control system efficiently updated the pump speed of the IRBP to avoid suction or overperfusion. In all scenarios, the numerical results for the left atrium pressure (Pla), aortic pressure (Pao), and left ventricle pressure (Plv) were clinically accepted. The Q^est accurately tracked the Qr within an error of 0.25 L/min.

Keywords

• heart failure
• proportional-integral
• fuzzy logic control
• estimator model
• rotary blood pump