Once escaped from the quiescence niche, precursor cells interact with stromal components that support their survival, proliferation, and differentiation. We examined interplays between human myogenic precursor cells (mpc) and monocyte/macrophages (MP), the main stromal cell type observed at site of muscle regeneration. mpc selectively and specifically attracted monocytes in vitro after their re...

This paper employs the Input-to-State Stability (ISS) framework to investigate the robustness of discrete-time Piece-Wise Affine (PWA) systems in closed-loop with Model Predictive Controllers (MPC), or hybrid MPC for short. We show via an example taken from literature that stabilizing hybrid MPC can generate MPC values functions that are not ISS Lyapunov functions for arbitrarily small additive...

Model Predictive Control (MPC) for buildings has gained a lot of attention recently. It has been shown that MPC can achieve significant energy savings in the range between 15-30% compared to a conventional control strategy, e.g., to a rule-based controller. However, there exist several reports showing that the performance of MPC can be inferior to that of a well-tuned conventional controller. P...

State-of-the-art baggage handling systems transport luggage in an automated way using destination coded vehicles (DCVs). These vehicles transport the bags at high speeds on a “mini” railway network. Currently, the networks are simple, with only a few junctions, since otherwise bottlenecks would be created at the junctions. This makes the system inefficient. In the research we conduct, more comp...

We provide an overview on the application of distributed and hierarchical model predictive control (MPC) algorithms for the power reference tracking problem of the HD-MPC Hydro Power Valley (HPV) system (Savorgnan and Diehl, 2011). Serving as a case study for distributed and hierarchical MPC, the HPV benchmark has various challenging features, including nonlinear, non-smooth, and coupled cost f...

State-of-the-art baggage handling systems transport luggage in an automated way using destination coded vehicles (DCVs). These vehicles transport the bags at high speeds on a “mini” railway network. Currently, the networks are simple, with only a few junctions, since otherwise bottlenecks would be created at the junctions. This makes the system inefficient. In the research we conduct, more comp...

The high cost of model predictive control (MPC) technology has hampered its wide application in process industries beyond the refining/petrochemical industry. This work aims to increase the efficiency of MPC deployment. First a semi-automatic MPC system is introduced. It consists of three modules: an MPC control module, an online identification module and a control monitor module. The goal of t...

Model predictive control (MPC) is a very popular controller design method in the process industry. An important advantage of MPC is that it allows the inclusion of constraints on the inputs and outputs. Usually MPC uses linear discretetime models. In this paper we extend MPC to a class of discrete event systems, i.e. we present an MPC framework for max-plus-linear systems. In general the result...

This paper focuses on developing a stochastic model predictive control (MPC) strategy based on Gaussian Processes (GPs) for propagating system disturbances in a receding horizon way. Using a probabilistic system representation, the state trajectories considering the influence of disturbances can be obtained through the uncertainty propagation by using GPs. This fact allows obtaining the confide...

Most academic control schemes for MIMO systems assume all the control variables are updated simultaneously. MPC outperforms other control strategies through its ability to deal with constraints. This requires on-line optimization, hence computational complexity can become an issue when applying MPC to complex systems with fast response times. The multiplexed MPC scheme described in this paper s...