Abstract：At present, there are few studies on the switching mechanism of double-hormone artificial pancreas subsystems, and existing studies need to be improved in terms of operation efficiency and group control quality. To solve the aboved problem, based on the three decision theory and model predictive control algorithm, a model predictive control algorithm of double-hormone artificial pancreas based on three-branch decision theory was proposed. The algorithm used the three decision theory to design the switching rules among the three subsystems. The rule calculated the decision risk value of switching to each subsystem by designing the cost matrix including economic cost and high and low blood sugar risk, so as to ensure the final switching to the subsystem with the minimum risk value. Finally, 33 virtual patients were experimented on a mature UVA simulation platform and the simulation results were analyzed from various aspects. It was proved that the mentioned algorithm could control blood glucose well within the normal range, and had achieved good results in tracking error, risk index, operation efficiency and group control quality of multiple patients.
孙超,孔雪华,高军,陆凯旋,杜鹏翔. 基于三支决策的双激素人工胰脏模型预测控制算法研究[J]. 计量学报, 2021, 42(5): 681-688.
SUN Chao,KONG Xue-hua,GAO Jun,LU Kai-xuan,DU Peng-xiang. Research on Model Predictive Control Algorithm of Double-hormone Artificial Pancreas Based on Three-branch Decision Theory. Acta Metrologica Sinica, 2021, 42(5): 681-688.
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2021, Vol. 42 
