We describe a method for embedding advanced weather disturbance models in model
predictive control (MPC) of energy consumption and climate management in buildings. The …

We report the closed-loop performance of adaptive model predictive control (MPC)
algorithms for a dual-hormone artificial pancreas (AP) intended for patients with type 1 …

People with type 1 diabetes (T1D) must estimate the carbohydrate (CHO) content in meals to
compute the bolus insulin correctly. To release T1D patients from the cumbersome task of …

This paper introduces a linear quadratic control scheme for a continuous-time system with
observations taken at discrete times. Particular attention is given to the derivation of the …

In this paper, we evaluate the closed-loop performance of two switching strategies for a dual-
hormone artificial pancreas (AP). The dual-hormone AP administers insulin and glucagon …

This paper addresses the problem of mathematical deconvolution for the estimation of
unknown inputs in linear discrete-time state-space models. We apply our deconvolution …

This paper presents an algorithm for Model Predictive Control of SISO systems. Based on a
quadratic objective in addition to (hard) input constraints it features soft upper as well as …

In this paper we present a linear model predictive control (MPC) algorithm for control of the
blood glucose concentration of critically ill patients in an intensive care unit (ICU). We …

To facilitate data-driven tuning of Kalman filter, we propose a control-oriented greybox noise
structure of multi-stage spray dryers. In the first step, we derive the noise structure by a …

This thesis focuses on the theoretical underpinnings of model predictive control (MPC) for
linear stochastic systems. The plant model comprises a deterministic and stochastic part …