Predicting the output error of the suboptimal state estimator to improve the performance of the MPC-based artificial pancreas
Martin Dodek
Eva Miklovičová
Institute of Robotics and Cybernetics,Faculty of Electrical Engineering and Information Technology,Slovak University of Technology in Bratislava,Ilkovičova 3,Bratislava 81219,Slovakia
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.
机标关键词：improvestateartificialerrorestimatormpc-basedoutputpancreas
论文发表日期：2023-11-05
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：14( 541-554 )
英文信息