activity
20172022
most citedA fast and memory-efficient spectral Galerkin scheme for distributed elliptic optimal control problems

2 citations · 8 across the 13 of their papers we have counts for

collaborators

15 papers

eess.SY20221 cited

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…

math.OC2022

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…

eess.SY20221 cited

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…

math.OC20221 cited

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…

eess.SY2022

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…

math.OC2022

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…