Predicting the output error of the suboptimal state estimator to improve the performance of the MPC-based artificial pancreas  

作　　者：Martin Dodek Eva Miklovičová 

机构地区：[1]Institute of Robotics and Cybernetics,Faculty of Electrical Engineering and Information Technology,Slovak University of Technology in Bratislava,Ilkovičova 3,Bratislava,81219,Slovakia

出　　处：《Control Theory and Technology》2023年第4期541-554,共14页控制理论与技术（英文版）

基　　金：supported by the grant VEGA 1/0049/20—Modelling and Control of Biosystems,the Ministry of Education,Science,Development and Sport of the Slovak Republic.

摘　　要：The error of single step-ahead output prediction is the information traditionally used to correct the state estimate while exploiting the new measurement of the system output.However,its dynamics and statistical properties can be further studied and exploited in other ways.It is known that in the case of suboptimal state estimation,this output prediction error forms a correlated sequence,hence it can be effectively predicted in real time.Such a suboptimal scenario is typical in applications where the process noise model is not known or it is uncertain.Therefore,the paper deals with the problems of analytical and empirical modeling,identification,and prediction of the output error of the suboptimal state estimator for the sake of improving the output prediction accuracy and ultimately the performance of the model predictive control.The improvements are validated on an empirical model of type 1 diabetes within an in-silico experiment focused on glycemia prediction and implementation of the MPC-based artificial pancreas.

关 键 词：Suboptimal state estimation PREDICTION Autoregressive model Moving average model Model predictive control Diabetes mellitus Artificial pancreas 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]