Flow profile generation for a left ventricular assist device using iterative learning control

Abstract

Abstract Nowadays, rotary blood pumps for the treatment of end-stage heart failure patients are usually fixed-speed controlled. Therefore, without sufficient heart activity, patients may reveal reduced blood flow pulsatility. However, there is evidence that pulsatile flow reduces adverse events. Furthermore, optimized pump flow profiles could be used to achieve certain control objectives. Therefore, a pump flow model is identified and subsequently used to design a control system with an iterative learning controller to generate desired pump flow patterns. Either a flow sensor is required for direct measurement or the flow can be estimated from pressure sensor readings using the proposed pump flow model. For comparison, a PID controller with disturbance feedforward control is also designed. Furthermore, the robustness against respiratory sinus arrhythmia is analyzed.