Non invasive measurements based model predictive control of pulsatile flow in an implantable rotary blood pump for heart failure patients
In this paper, firstly, we propose a linear time variant (LTV) model to estimate the mean pulsatile flow (Qp) in an implantable rotary blood pump (RBP) Non invasive measurement of mean pulse width modulation (PWM) signal acquired from the pump controller was used as an input to estimate the mean pulsatility index of pump rotational speed (PIo) with this subsequently used to estimate the mean Qp. Secondly, the proposed LTV model was used to develop a controller to regulate and track the variations in the mean Qp and PIo. We used a model predictive control (MPC) approach to develop the controller where this allowed us to explicitly apply pre defined practical constraints to control input PWM as well as the output and the states of the system including; Qp and PIo. The model and the controller were tested using a parameter optimized model of the cardiovascular system rotary blood pump under wide ranges of speed ramp experiments carried out under different operating conditions such as variations in afterload, preload and heart contractility.
2011 19th Mediterranean Conference on Control Automation (MED)