LAUSR

This article presents a semiparametric model-based adaptive control method for the regulation of aortic pressure (AoP) in an ex situ heart perfusion (ESHP) system. The semiparameter dynamic model of the perfusion system includes a three-element model with a capacitor and two resistors to describe the reference relationship between the AoP and perfusion flow, and a data-driven model to describe the nonlinearity and the uncertainty of the perfusion system. This semiparametric model gains high accuracy of ESHP model parameters with small size of samples in real time. We integrate the semiparametric model in an adaptive controller, which tunes the control parameters based on the personalized ESHP model to regulate the AoP to maintain the heart's physiological aerobic metabolism. Simulations and experiments (55$\pm$5 kg pigs, $n=6$) show that the proposed semiparametric model achieved high accuracy (0.04 mmHg), ESHP model personalization in real time (0.55$\pm$0.23 s), and a small overshoot less than 2 mmHg.