Simulation software for assessment of nonlinear and adaptive multivariable control algorithms: Glucose–insulin dynamics in Type 1 diabetes. (2nd November 2019)

• Record Type: Journal Article
• Authors: Rashid, Mudassir; Samadi, Sediqeh; Sevil, Mert; Hajizadeh, Iman; Kolodziej, Paul; Hobbs, Nicole; Maloney, Zacharie; Brandt, Rachel; Feng, Jianyuan; Park, Minsun; Quinn, Laurie; Cinar, Ali
• Is Part Of: Computers & chemical engineering. Volume 130(2019)
• Publication Date: 2019-11-02
• Subjects: Multivariable simulator -- Benchmark testbed process -- Time-varying uncertain nonlinear system -- Nonlinear and adaptive model predictive control -- Biomedical application; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2019.106565
• Languages: English
• ISSNs: 0098-1354

Abstract

Abstract: A simulator for testing automatic control algorithms for nonlinear systems with time-varying parameters, variable time delays, and uncertainties is developed. It is based on simulation of virtual patients with Type 1 diabetes (T1D). Nonlinear models are developed to describe glucose concentration (GC) variations based on user-defined scenarios for meal consumption, insulin administration, and physical activity. They compute GC values and physiological variables, such as heart rate, skin temperature, accelerometer, and energy expenditure, that are indicative of physical activities affecting GC dynamics. This is the first simulator designed for assessment of multivariable controllers that consider supplemental physiological variables in addition to GC measurements to improve glycemic control. Virtual patients are generated from distributions of identified model parameters using clinical data. The simulator will enable testing and evaluation of new control algorithms proposed for automated insulin delivery as well as various control algorithms for nonlinear systems with uncertainties, time-varying parameters and delays.