近期，实验室教师姚蔚然作为第一作者的论文“Semi-Parametric Model-Based Adaptive Control for Aortic Pressure Regulation in ex situ Heart Perfusion”被国际权威期刊IEEE Transactions on Industrial Electronics录用。

论文针对体外心脏灌注中的主动脉压力调节问题提出了一种基于半参数模型的自适应控制方法。心脏灌注的半参数动态模型包括一个带有电容器和两个电阻器的三元模型用于描述主动脉压力和灌注流量之间的参考关系，同时基于数据驱动模型描述灌注系统的非线性和不确定性。该半参数模型实时获得了小样本量的ESHP模型参数的高精度。我们将半参数模型集成到自适应控制器中，该控制器能够动态调节ESHP模型控制参数，实现主动脉压力的有效控制，以维持心脏的生理有氧代谢。仿真和实验（55±5 kg猪样本，n=6）表明，提出的半参数模型实现了高精度（0.04 mmHg）ESHP模型的实时个性化（0.55±0.23 s），超调量小于2 mmHg。

Abstract

This paper presents a semi-parametric model-based adaptive control method for the regulation of aortic pressure (AoP) in an ex situ heart perfusion (ESHP) system. The semi-parameter dynamic model of the perfusion system includes a three-element model with a capacitor and two resistors to describe the reference relationship between the aortic pressure and perfusion flow, and a data-driven model to describe the nonlinearity and the uncertainty of the perfusion system. This semi-parametric model gains high accuracy of ESHP model parameters with small size of samples in real time. We integrate the semi-parametric 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±5 kg pigs, n=6) show that the proposed semi-parametric model achieved high accuracy (0.04 mmHg) ESHP model personalization in real time (0.55±0.23 s) with a small overshoot less than 2 mmHg.