7 citations · 20 across the 23 of their papers we have counts for
13 papers · 1 filter
Modeling, scientific computing and optimal control for renewable energy systems with storage
Nicola Cantisani, Tobias K. S. Ritschel, Christian A. Thilker +2
This paper presents models for renewable energy systems with storage, and considers its optimal operation. We model and simulate wind and solar power production using stochastic di…
Model-based control algorithms for the quadruple tank system: An experimental comparison
Anders H. D. Andersen, Tobias K. S. Ritschel, Steen Hørsholt +2
We compare the performance of proportional-integral-derivative (PID) control, linear model predictive control (LMPC), and nonlinear model predictive control (NMPC) for a physical s…
Modelling and Economic Optimal Control for a Laboratory-scale Continuous Stirred Tank Reactor for Single-cell Protein Production
Marcus Krogh Nielsen, Jens Dynesen, Jess Dragheim +5
In this paper, we present a novel kinetic growth model for the micro-organism \textit{Methylococcus capsulatus} (Bath) that couples growth and pH. We apply growth kinetics in a mod…
Model Predictive Control Tuning by Monte Carlo Simulation and Controller Matching
Morten Ryberg Wahlgreen, John Bagterp Jørgensen, Mario Zanon
This paper presents a systematic method for the selection of the Model Predictive Control (MPC) stage cost. We match the MPC feedback law to a proportional-integral (PI) controller…
State Estimation for Continuous-Discrete-Time Nonlinear Stochastic Systems
Marcus Krogh Nielsen, Tobias K. S. Ritschel, Ib Christensen +4
State estimation incorporates the feedback in optimization based advanced process control systems and is very important for the performance of model predictive control. We describe…
Performance Quantification of a Nonlinear Model Predictive Controller by Parallel Monte Carlo Simulations of a Closed-loop System
Morten Wahlgreen Kaysfeld, Mario Zanon, John Bagterp Jørgensen
This paper presents a parallel Monte Carlo simulation based performance quantification method for nonlinear model predictive control (NMPC) in closed-loop. The method provides dist…
Estimating a Personalized Basal Insulin Dose from Short-Term Closed-Loop Data in Type 2 Diabetes
Sarah Ellinor Engell, Tinna Björk Aradóttir, Tobias K. S. Ritschel +2
In type 2 diabetes (T2D) treatment, finding a safe and effective basal insulin dose is a challenge. The dose-response is highly individual and to ensure safety, people with T2D tit…
State Estimation Methods for Continuous-Discrete Nonlinear Systems involving Stochastic Differential Equations
Marcus Krogh Nielsen, Tobias K. S. Ritschel, Ib Christensen +4
In this work, we present methods for state estimation in continuous-discrete nonlinear systems involving stochastic differential equations. We present the extended Kalman filter, t…
A whole-body multi-scale mathematical model for dynamic simulation of the metabolism in man
Peter Emil Carstensen, Jacob Bendsen, Asbjørn Thode Reenberg +2
We propose a whole-body model of the metabolism in man as well as a generalized approach for modeling metabolic networks. Using this approach, we are able to write a large metaboli…
Large-scale Virtual Clinical Trials of Closed-loop Treatments for People with Type 1 Diabetes
Tobias K. S. Ritschel, Asbjørn Thode Reenberg, John Bagterp Jørgensen
We propose a virtual clinical trial for assessing the safety and efficacy of closed-loop diabetes treatments prior to an actual clinical trial. Such virtual trials enable rapid and…
Nonlinear Model Predictive Control and System Identification for a Dual-hormone Artificial Pancreas
Asbjørn Thode Reenberg, Tobias K. S. Ritschel, Emilie B. Lindkvist +5
In this work, we present a switching nonlinear model predictive control (NMPC) algorithm for a dual-hormone artificial pancreas (AP), and we use maximum likelihood estimation (MLE)…
High-performance Uncertainty Quantification in Large-scale Virtual Clinical Trials of Closed-loop Diabetes Treatment
Asbjørn Thode Reenberg, Tobias K. S. Ritschel, Bernd Dammann +1
In this paper, we propose a virtual clinical trial for assessing the performance and identifying risks in closed-loop diabetes treatments. Virtual clinical trials enable fast and r…
A one-size-fits-all artificial pancreas for people with type 1 diabetes based on physiological insight and feedback control
Tobias K. S. Ritschel, Asbjørn Thode Reenberg, Emilie B. Lindkvist +6
We propose a model-free artificial pancreas (AP) for people with type 1 diabetes. The algorithmic parameters are tuned to a virtual population of 1,000,000 individuals, and the AP…